IBM Netezza Performance Server Reviews

Our use case is, we use Netezza as a data warehouse and for analytics.  

We have sub-second query performance, and users are happy with the product.

Row-secure tables, IBM Fluid Query, and others.

This is an appliance-based product with limited capability. It has all the horse-power that one can imagine and can handle all workloads.

The performance is most important to me, and it helps our ability to make business decisions quickly.

They should make it work better in a multi-user context. This solution works, but not for the workload we have.

It is stable. We use it in our data warehousing complex, and the performance is good.

The scalability is not as expected. It is shipped to you as an appliance, a black box. If you want to expand it, you have to get an extra CD,or whatever, and they come and program something int he box to release extra bits. If this were a cloud product, you could just expand and subtract as you wish. The capacity in this black box is not enough.

I would rate the tech support a five, on a scale of one to ten. It is obviously not that great. 

We had Teradata before, and I am not really sure why we switched.

Based on first conception, do a POC, scale up to the volumes and get the vendor to prove that it can work with their requirements. Get them to scale it up, either simulate it, make sure it can actually do what it says, rather than buying beta and then get it and then find out that it doesn't actually do everything it says it does.

We use it primarily for analytics.

Over 90 percent of our query executions are one second or less. We do millions of queries everyday.

• It is hands-off when everything works well. 
• We are able to execute very complex queries.
• It has good performance.

Our main problem with it is concurrency. When there are too many users running Netezza at the same time, this is when we have the most complaints.

Stability-wise, the product has improved. Netezza has improved the product over the past 10 years. We now have better monitoring and can be more proactive about detecting issues.

We have come to the point where we need to watch out for our capacity, as we are adding more users onboard with Netezza. We are not able to scale. The only way to scale is to get another appliance, but we have a customers who would need us to hydrate the data between the two appliances, and Netezza does not do that.

We are looking at the cloud approach, but we still have applications on-premise that we have to support.

The technical support has degraded overtime, especially after Netezza was bought by IBM. It appears as if some of the Netezza's SMEs left after IBM bought them.

We were previously using Oracle Database. We switched for performance reasons and running complex queries. Compared to Oracle, Netezza has superior performance.

The initial setup was very complex. However, this can be attributed to our environment and the complexity of the business which we process.

The pricing is very expensive. It has a lot CPUs with a lot of components in it. It also has built-in redundancy for resiliency reasons. I believe that's why it is so expensive.

We did look at some other analytics platforms a few years back.

We are now looking at solutions due to scalability, such as: Db2 Warehouse, Exadata, Teradata, and Yellow Brick. Then, on the cloud side, we are considering Redshift and Snowflake.

Get the requirements and have them finalized. Then, be very specific about the requirements that your organization needs. Based upon your requirements:

1. Identify whether Netezza will be suitable for your requirements. 
2. Get the sizing right.

Our prime use is for warehousing and analytics.

Being an appliance, the best features are its analytics and the performance level.

The underlying hardware that IBM provides with this appliance is made for a specific purpose, to serve performance on a large amount of data, and to do analytics as well. It is faster, when you compare it to any other product, like Hadoop or DXC Hadoop or Presto on AWS. It's made for a specific purpose and it serves that very appropriately.

It really serves its purpose. It meets the need for performance, it meets the need for robustness, and it also serves as a perfect data warehousing appliance. The only issue is that it's not expandable.

The new versions of Netezza, they are expandable. They can be on-prem and on the cloud like dashDB from IBM. It replaces the previous Netezza versions. We are currently on Mako because TwinFin support is going in 2019. Maybe in the next couple of years, we will be replacing Netezza with Redshift.

As a database administrator, and in warehousing part for the last 12 years, we always have stability issues in every technology. So the issue is how well they support their product. IBM does support their product very well. We have had issues where there were queries that were generating billions of rows. It's all about how you understand the underlying architecture. The coder who understands the architecture can write a better query. We sometimes need to educate them. So there are always stability issues but not in terms of hardware or support. It's always how well you write your queries.

If you don't know Netezza, if you don't SQL or you don't know the underlying architecture but you are a good SQL developer, you know all the business logic and you write a query - but it is not actually performing - it's because you have not understood the distribution part of it. You need to consider the distribution keys or the organization keys. That makes the difference.

The stability doesn't depend on the hardware, it depends on your coding in SQL.

If I was using TwinFin appliances, if my data grew to the limit that TwinFin supports, obviously I would have to buy a new appliance. I cannot just ask them to increase the memory or increase the storage or the CPUs. That would cost me another appliance. If our business side agreed to that, I would keep using Netezza and buy a bigger appliance, I'm okay with that. But the expandability is not there.

I would rate the technical support at seven out of 10. We have our own SLAs and they have their own SLAs and things go around that. If we want to a fix in two days, it might be that they are not able to provide it, until it becomes business critical.

Netezza was the first one which we incorporated and started using heavily. Before that, we did test the other data warehousing technology but it was just a PoC and PoV test.

In some of our business areas, they still use SQL Server data warehouses and Oracle data warehouses. But once we moved to Netezza, different business units bought in, and now we are up to Hadoop solutions and AWS solutions.

Once it has been shipped and installed in your data center, it's just the point of plugging it in and the initial configuration. IBM people come and when they install it, they initialize it and then they give us the password and from there we move on in. It's very simple from there.

Netezza is a costly solution. It does serve a specific purpose but it's costlier than what's available in the market, if you go to the cloud.

We are also doing a proof of value and proof of concept for AWS and Hadoop DXC.

My client is looking towards replacing Neteeza with one of the up and coming warehousing solutions like Presto. They don't want the in-house or on-prem cost of managing that particular appliance. When everything is available on cloud, we pay less. My client develops medical products. They wanted to concentrate on the medical part, not on how to manage their IT. So they're moving towards more and more towards the cloud to replace the on-prem solution.

My advice would be to fully categorize your needs. Why you need Netezza should be a specific question, because there are so many different analytic solutions and which provide performance and which are cheaper than Netezza. Until you figure out completely that you only need a PDA (pure data analytics) system, you should really look at other products and compare them.

I wouldn't choose Netezza in today's world when we have Redshift, Presto, EMR, when we have Teradata, and when we have Oracle Autonomous. In today's world, you should look at these solutions first. If they don't serve your purpose, then look to Netezza.

In the current world, data is the big question. Nowadays, we are receiving a lot of data. It's like the data generation has come. We have terabytes of data and it might be, in a year or so, you cross the petabyte scale. So go with a petabyte-scale solution instead of a non-expandable Netezza appliance.

We are currently working on the latest Mako version. After that - Mako retires in 2024 - I don't think they have anything on Netezza. What they have is dashDB and Sailfish, which is a completely different product for IBM, but similar to Netezza. And those are expandable.

Netezza is a good product in and of itself, aside from the fact it is not expandable. Overall, it's a good product but definitely has room for improvement.

Neteeza is a data warehouse for customer analytics. 

We're looking to get away from it, so I can't really say that it improved things. It did augment some of our product delivery resources.

The most valuable feature would be the fact that it has been running for awhile in an appliance format. The appliance format may be the best part.

There won't be another release. They're converting to DB2 and that is one of the reasons we are looking at other options.

In terms of features that I would like to see, one is the ability to actually scale out an architecture. Right now, if you buy one, it's fixed. There is no scale-up availability at all.

It's pretty good when it works. It's pretty stable overall. But if you have a problem, support is a nightmare.

Scalability is not possible.

Technical support has been awful. I found them unwilling to help, and with direct VPN connection to systems, unwilling to actually connect and look at information, which is part of our contract. They did not actually do their job.

We're looking to switch away from Netezza because the platform database system that it runs on is no longer going to be in existence. It's moving to DB2. If it moves to that direction, the amount of changes in logic and queries that it would require is pretty substantial. At that point I would basically be rewriting everything.

When selecting a vendor, obviously I don't want somebody who is brand new. I want somebody who has a track record of actually being around for awhile. It needs to be a company with a product that does the functions that a database should do, and not something that's only a partial solution. There are a lot of solutions out there that do three-quarters of what a warehouse should be doing, but three-quarters of a warehouse are not sufficient.

I wasn't involved in the setup. But it's an appliance, so there is no real setup, other than there is a day for an IBM technician to come out and stand it up.

Vertica was one of them. I looked at it recently. It has limiting factors on things like updates and deletes of data, where it has performance issues. That's a big problem for us. 

I rate Netezza at four out of 10. There is not too much involved to set one up from a customer perspective, but after the initial setup it is pretty awful on the customer support side of it.

My advice would be, check out all options. Don't just go with big-name vendors, because that is not always going to be the right answer.

For now, we use that as our enterprise-wide data warehouse. Performance-wise, it's been great. The speed has been excellent. We haven't really had any hardware issues with it that I'm aware of. We've had it for heavy-use in the past six months to a year. It's been good.

The big benefit that we've had is, in the past with the legacy data warehouse solution, we've been limited to having just a nightly batch, running on SQL Server. It's a slower batch process, so throughout the day we would be limited to stuff that happened as of some time in the evening. 

So the benefit is really because of the additional speed that we have and, truth be told, the more updated ETL processes and the revamped scheduler in general. We've been able to move the refresh timing up to six times a day, so at any given point in the day, the data would be only four hours old, which helps us give much better - not quite real-time data - but closer to real-time data for the day, which helps the decision-makers get the most up-to-date information possible.

The speed.

I would say it's very stable. Whenever we have any sort of outage, the hardware team always communicates it, and it's been months since we've had any sort of outage, outside of the standard maintenance window. There have never really been any issues there. Stability has been good.

For scalability, we're still in process - half the business is still not on this data warehouse, the company is also moving over to a different production system - so the scalability, we'll really see throughout this year, as the rest of the business gets migrated over to that new production system, and that data will be falling into the Netezza data warehouse platform. So for scalability, it's a little too soon to really give an answer yet.

I have not used tech support. I'm not on the hardware team.

Our IT leadership made the decision to go with Netezza before I joined the company, that decision had already been made. Prior to that we were using Microsoft SQL Server.

The only thing that I was really privy to was, Netezza was chosen because of its analytical capabilities and for the ability to process through a very high volume of records and give an aggregate solution from an analysis standpoint, in a very quick fashion.

I was not involved on the hardware side, but I was on the data modeling aspect.

I would say it was straightforward. We used the IBM InfoSphere for the ETL scripts. Those seem to give plenty of visibility for allthe different steps in the ETL process, especially debugging or going in and making modifications as different tickets come through.

Working with some of the other developers, whenever they are given a ticket, it's pretty simple to see what step in the process and additional code needs to be added, or modified, or removed; to see exactly where it is and how it's going to affect things downstream, and to be able to see at what exact point that something has failed. That part, it's been more straightforward and just the visibility of the whole process.

The most important criteria when selecting a vendor for a data warehouse solution are, obviously, the speed and the ability to handle large amounts of data. That's especially true from an analysis standpoint, and having it not only do the math and select statements but also do more aggregation and analysis-type queries.

The speed has been excellent for us, in pulling information, as well as the batch timing, and the suite of tools that comes with it for the ETL withIBM InfoSphere. Also, the data governance prospect, as a company we haven't really delved too far into that, but from what I've seen, that is a really powerful tool as well, to help with data lineage and keeping track of that. So the speed is good and the suite of tools seems to be very beneficial.

From my standpoint, I would give it a nine out of 10. It has done everything that we needed it to do, it's great. The only reason I wouldn't give it a 10 is because, early on, there were a couple of maintenance things that we had to do.

We use Netezza and Teradata in our project environment where I work as an admin and data modeler.

Distribution concurrency control.

Concurrency limit needs to be increased somewhat.

Great stability in Netazza's Mako.

As of now, no issues with scalability. But like Teradata, we can’t add a node/SPU to the existing appliance.

I work with IBM PDA support. They are wonderful and fix issues in good time.

We used Teradata for Data Mart for certain applications but issues arose once the data setup grew. Using PDA, the issues were resolved.

Setup is not that complex. Within 24 hours we had everything completed and had copied the dataset from Oracle. Our migration approach was to use a shell script (pipe).

Best if you have a robust infrastructure, where network bandwidth is good. We used 10GB Ethernet cable for data transfer.

Enterprise reporting data warehouse using Business Objects, Microstrategy and data mining using SQL. Being a data repository for a single customer view. Also contained staging tables, some of which were designed like an ODS and contained all data from the source system and was updated on a nightly basis. The applicance contained over 12 TB of data uncompressed (less than 4 TB compressed).

Reports which used to take between 30 to 60 minutes or would time out on an Oracle database, which was previously used for the enterprise DWH, now run consistently in seconds or in less than five minutes.

High performance RDBMS appliance optimized for data warehousing and enterprise reporting. Very simple to manage huge volumes of data without having to worry about indexing and partitioning. Automated compression of tables without any custom scripting or manual intervention. Achieved almost 3x compression effortlessly which meant that 12 TB of data compressed into around 4 TB.

Could do better to support more concurrent update queries. We had to stagger our ETL loads to prevent queuing of jobs and random failures.

Also, it would have been good if the admin application showed more detail on the validity and usage of zone maps (this may have been implemented in later versions of the admin app).

The database runs stable unless there are hundreds of queries running in parallel.

Every query is a full table scan. If the table contains mostly integers, then performance is good. If the number of users is in the thousands, then it may be better to use cubes or other solutions to service reporting needs.

Before being acquired by IBM, Netezza corporation had exceptional support and used to respond very quickly (less than 30 minutes) in case of production issues. Round the clock support and monitoring were offered and support tickets were handed over very professionally between engineers working across time zones. After being acquired by IBM, support has not been as responsive, but there weren't as many issues as the box was stable.

Previously, Oracle was used as the data warehousing platform, and performance was low and not meeting the needs of the enterprise reporting and analytic user community. My customer switched to Netezza mainly for performance, and it was a big improvement.

As the box was very heavy, datacenter flooring required additional reinforcement. The box runs Linux and the initial setup is quite straightforward. ODBC drivers on the servers (ETL or reporting) which connect to the box may need to be upgraded.

Implemented this through a vendor team. As there is no need to spend time on partitioning and indexing, a lot of vendor time was saved. Table scripts for partitioned oracle tables run into hundreds or thousands of lines of code and we used to be charged accordingly. But a Netezza table script is much much simpler and we saved money there. Review of table scripts for performance and best practice was also easier as there is only a limited set of best practices to be implemented for high performance. So even vendor teams having low or medium level of expertise can deliver properly as long as they understand how MPP works - governance effort is definitely lesser with Netezza compared to Oracle or SQL Server.

ROI is high because analyst productivity improved drastically. As mentioned before, queries which used to run for several minutes now run in seconds or less than a few minutes or the duration of a typical pop song. So analysts can ask more questions of the data per hour compared to Oracle.

Also, the compression feature saved us a lot of money on per terabyte costs for the data.

From a cost per terabyte perspective, Netezza is definitely more expensive compared to Hive on Hadoop, but due to its simplicity and ANSI SQL Compliance and high performance which can be achieved with less tuning, it may be worth it.

My customer upgraded from Netezza 4.x to Twinfin 6.x.

Netezza is a great option for data warehousing, but give due attention to concurrency and find out how much would be the peak load the database may have to handle. Also, check whether performance is acceptable for APIs and web services. Performance may not scale for thousands of single row lookups, as the database is more suited for complex aggregated data warehousing queries.

It is extremely easy to use. The platform is very efficient and robust as well.

Generally, the machine utilized for the PoC is rarely returned once the overwhelming results are seen! Customers decide to keep the project, almost from scratch! The initial KPIs are delivered with low investment. There is quick implementation and considerable outcomes which make the platform a valuable asset to the organization.

Marketing, I dare say, should be improved. The ads should never mention “big data” since the platform was not initially designed for it.

I worked years and years ago with Teradata, and this is the platform to which it should be compared. It is important to emphasize that Netezza and Teradata have different markets. Netezza performs very well “in its peculiar and valuable small world.”

I have used this solution for years.

We did not have any stability issues.

It is not designed to process a huge volume of data.

Technical support is good.

I worked for different companies and my experience is really wide. Teradata is the paramount solution! Oracle’s Exadata invests a lot in both technology and marketing, sometimes losing the focus on “real” analytics. They used to address the platform as both OLAP and OLTP (“one size fits all”), which is not correct.

The rule of thumb in the data warehousing/business intelligence space starts with a simple PoC. That being said, there must be a few questions to be answered by the platform. The data model must be simple and flexible enough to address some “extra questions” within a set timetable, in case the customer wants to extend the PoC prior to making the purchase.

Comparisons with other solutions, including pricing and licensing, is as important as a PoC.

I compared Netezza to Teradata and Exadata.

IBM PureSystems or NPS has a patented NDAC or Netezza data accelerator card inside each of the SPUs (Snippet Processing Arrays). The SPUs act as individual processors that share part of a query. This helps in high-speed parallel processing of big data volumes. Querying a large data volume takes just a few seconds to minutes, if it is done right.

Analyzing years of data requires high processing power and storage. IBM PDA has exactly that. Years of processed data (tables) can be queried and retrieved based on management requirements. This can be done in minutes for analysis. This is extremely important in identifying trends for decision making in higher management, to serve customers better in today’s business environment.

It is a highly complicated architecture and only IBM engineers/support, or someone who worked on the hardware side of the system, can understand the system architecture completely.

This means that:

• Replacements can only be done by an IBM engineer
• Components are not generic and are not on the market
• Many of the systems are IBM patented
• Service support costs are high

Storage, although high, is limited depending on the rack configuration. For example, an N3001-80, which is an eight-rack Mako Server and also the top end model with the highest storage, can store a maximum of 384TB. Should your data exceed this limit, the storage cannot be extended.

It cannot be used for unprocessed data. The data has to be in a table format.

We have been using the solution for five years.

We rarely had stability issues. You may expect an average of one outage every two months for a few minutes, if it is maintained properly. This is mostly due to “pollreplytimeout” errors of the SPU.

All the rack components are dual for redundancy. Almost all components have failsafe/backup, including the host that is configured in cluster for high availability. With this, the system is up and running all the time, or you can get it up at the earliest possible time in case of component failures/system down situations.

We had scalability issues. Storage, although high, is limited depending on the rack configuration. For example, an N3001-80, which is an eight-rack Mako Server and also the top end model with the highest storage capacity, can store a maximum of 384TB. Should your data exceed this limit, the storage cannot be extended. You will have to purchase a new appliance.

I would rate the technical support at 7/10.

We did not use a previous solution.

IBM sets up the NPS and does the initial configurations. As an admin, you will have a completely configured system ready to work on.

This is a multi-million dollar product. The software and hardware are both IBM patented.

Netezza SQL ('nzsql') runs only on PDA systems, and cannot be installed on other enterprise-class servers. Power consumption is high and these systems must have mandatory IBM support, due to the patented and exclusive IBM hardware. However, the benefits outweigh the costs if you have large data volumes that require fast analysis on a day-to-day basis.

We didn't really examine any alternatives. I started working directly on IBM PDA (Netezza) and I haven't had any chance to work on the competitors' products. I was not a decision maker in the selection of this product. This was a higher management decision.

A close competitor of IBM PDA is Apache Hadoop. As of now, no other product is as fast or as stable.

You can definitely consider this appliance if you have:

• A large volume of processed data (tables) that are created on a daily basis
• Data that requires daily analysis, critical for decision making, and a budget to complement it.

This is one of the most stable and fastest data warehouse appliances available in the market today.

Distribution (no index or partition), built-in analytics is a major advantange.

It has improved our management information systems and reporting capabilities.

It should also consider cloud based solutions.

We have been using the solution for more than ten years from the 8000 series,

We did not encounter any issues with stability.

I can't extend the storage, only up to 6x compress of data. You need to plan this when selecting the right product to buy.

Netezza support is good.

We used Oracle previously. The performance required less maintenance when comparing index and data maintenance issues.

The setup took only a few hours with all built-in apps. It is very quick and easy to use.

One license and one support, also cheaper compared to other products.

We evaluated MS SQL server.

It is easy to use. Make sure you select the right ETL and reporting tool. Also select the right tool for the organization to hold it in the long run.

It has a compression engine and FPGA on but you should still analyze your volume of data and decide on the right model and size.

We use Aginity to access Netezza database. We really like the way we can dominate the physical distribution of the data hence know how to improve the performance of the query. Netezza on its own is very fast which makes our life easier to run huge queries for analytics.

This has really helped us to improve the performance of our Data Marts and warehouses. We can run our reports very quickly. It has also improved the turn around time of business requests. 

In Aginity there should be a way to format the SQL queries. I think we can't format the query the way we can do it in Oracle editor (beautifier). Say, for example, if we are trying to get the DDL of an existing view, we lost the formatting. It's a minor issue, but important from usability point of view. Other than this, I think we are good so far with Netezza as a whole.

We have been using this product from last 5 years. 

We did not experience any issues.

We haven't had any issues.

We've not experienced any issues.

If volume is the issue, use Netezza. Nothing is better than this product.

• Supports both business intelligence and advanced analytics
• Efficient even if being used by thousands of users at the same time
• Streaming architecture based on blades
• Compatible with the most popular business intelligence and analytic tools
• Standard SQL, ODBC, JDBC, and OLE DB interfaces

We had lot of POC's on data warehousing project with the help of Netezza, we have proved that it has really improved time on doing analytics

I have used this solution for more than two years

There were no issues with the deployment.

It's reliable and available, with 99.99% uptime.

There were no issues with the scalability.

Support for this product is good.

Initial set-up was straightforward.

It was done by an in-house team.

It is good product if you are choosing to go for datawarehouse business intelligence.

• The speed of the MPP platform
• The ability to load large amounts of data in very short order
• The fact that the hardware and software are designed to work together and are supported in unison by IBM

We can process through more data much faster than we could with prior technologies.

More monitoring tools would be nice. I have found no tools within the tool which help with long running query issues. I would like to see the ability of static binds so access path can be counted on.

I've been using this since 2010

There were no issues with the deployment.

Stability comes and goes. Every software upgrade removes some problems, but introduces others. None have been critical, though.

There were no issues with the scalability.

It's 7/10 as when something goes wrong within IBM, it can take quite a bit to get it straightened out including a phone call to the sales rep to light fires.

It was a straightforward set-up. You just have to install the appliance, turn it on, and you can start using.

Netezza themselves set up the machines. We implemented our business rules using a vendor team to get us up to speed on MPP processing.

We evaluated this and Greenplum. Netezza won the battle for being an appliance that is wholly supported by the vendor. Greenplum won the individual transaction battle, but it was not enough to overcome the ease of an appliance.

The most difficult time I have with people is getting them to understand that Netezza is not meant for individual transactions, but for full set processing.

• Elimination of space management with less time spent on capacity planning
• Push down optimization through the use of FPGA to limit data at the storage layer
• The concept of an appliance where everything is pre-built (storage, hardware, database and OS) and the support for each of these components is through one vendor.

Query and process response times have improved resulting in customers being able to process and analyse more in less time.

Certain database maintenance tasks related to the catalogue need for the database to be offline. Enabling those tasks to be done with the database on-line would be beneficial. Also, the availability of additional SQL and database tuning options would be good.

I've used it for six years. We currently use the Mako, TwinFin-6 and TwinFin-3 appliances.

Deployment is straightforward.

The appliance is stable for the most part. All components have fail-over/spare components built-in. Any failed component is replaced within 24 hours by IBM support.

Since it is an appliance, individual components within the appliance cannot be scaled. Scaling would mean buying the next generation of the appliance.

7/10

7/10

Our previous solution was in Oracle which had a custom data model. The reason for the change in technology was due to the data model. The new data model was purchased from IBM and their recommendation was to use Netezza for it.

The hardware set-up is straightforward.

It is done by IBM support in a day or two. The use of the appliance to implement the data model require for knowledgeable development and database resources. Prior working knowledge of Netezza would be an added advantage.

IBM offers great pricing on refurbished appliances. These appliances are just like new but can be negotiated to be offered at much lower prices.

Resources who have previously worked with Netezza should be asked to work on the project. If people with prior Netezza knowledge cannot be engaged then candidates who are familiar with Linux should be sent for Netezza training offered by IBM prior to engaging them to work on this platform.

The ability to support a lot of complex queries to analyze rather big data sets at the same time is a valuable feature for us.

Netezza appliances are used on several key areas such as customer analytics, pricing, predictable analytics and forecasting, and reporting etc. The platform is really versatile and cost effective.

Data lineage on column or even object level does not exist, therefore external applications have to be used

We've been using it for three to four years.

There were no issues deploying it.

It is generally a reliable and stable platform.

There were no issues scaling it.

As a developer I am not dealing with IBM customer service related activities.

As a developer I am not dealing with IBM customer service related activities

No other solution was used previously.

I was not part of the initial set up but I know that the main challenge was to set up IBM CDC to transfer data to the Netezza appliance

No other solutions were looked at.

Netezza partitions all database objects across all available SPU’s. With traditional RDBMS systems, partitioning database objects requires a lot of planning and configuration. Netezza, only requires to develop a partitioning scheme. This eliminates several steps in the process, vastly simplifies performance tuning leading to very high performance.

As the system is preconfigured, the site level configuration required is minimal. Eliminates the need for a separate SAN.

Reduces system administration and database administration effort. Simplifies performance tuning effort. The net effect is reduced load on DBA team and quicker turnaround.

Application development in Netezza is done using SQL scripts and stored procedures. GUI based ETL tools provides higher level of visibility and higher productivity. I hope to see a GUI based application development environment. This could also be achieved through tight integration with an ETL tool, like IBM’s own ETL tool DataStage.

We've used it for five years.

Netezza was one of the components in our application. This component had the least number of issues

Netezza was one of the components in our application. This component had the least number of issues

Netezza was one of the components in our application. This component had the least number of issues

Good. We had Netezza experts assigned to the client site and had easy access to them.

1. Compared to other RDBMS, Netezza provides much higher performance and much lower maintenance effort
2. Compared to Teradata, lower cost and lower administration

Initial set-up of the system is quite simple. Eliminates several steps required in a custom built platform, like storage system configuration, planning database storage.

I was a consultant from the system implementation vendor.

1. Netezza is well suited for data warehousing and analytics, not for OLTP application
2. The key approach is to develop an uniform data distribution scheme and collocation of data partitions across related database objects. For example, if we have a large customer dimension and a large sales by customer fact, these tables will be joined very frequently. To get the best performance, both tables should be distributed on the same key, e.g. customer_id.

• Lots of space
• Implicit compression
• High Availability with multiple redundancy

The performance has meant that we reclaimed many hours in our batch window. The ease of which we ported data onto it, the fact that it does not take a lot of administration and the overall manageability of the box have improved our company.

Ability to use constraints to enforce uniqueness would be an improvement.

We got our first Netezza box in 2004 and the Pure Data in 2014 following the acquisition by IBM.

A blade failure at the commissioning stage, but the box (and predecessors) have been extremely stable and provides us with lots of scalability.

Very good for this product. It was excellent when it was Netezza and that support seems to have continued with IBM.

Previously used DB2 LUW but this could not provide us with the performance we needed at the time. We looked at Netezza as they were trying to get a foothold in the UK and the portability of data and the speed with which it performed was incredible.

Very straightforward for Pure Data but the initial set-up was affected by the fact that we seemed to get a junior technician from IBM who was not as good as other engineers we have had.

Build a strong relationship with your technical account manager as you will be referring to them quite a lot. Could save many man hours in the long term.

I can't comment on the figures but needless to say it has been a resounding success for us.

IBM support is very good for this product. It has very few issues and it does exactly what it says on the tin. Check for the functional limitations of the logical database e.g there are no such thing as indexes/primary key constraints where you might want to force uniqueness.

• Ease of use
• Lack of performance problems for analytics and massive data systems
• Integration with Linux-based ETL and data streaming technologies
• Integration with distributed computing platforms

It has been the primary driving technology behind the corporate wide transition to Netezza as a standard data platform. A whole ecosystem is beginning to develop around the product.

It is not designed for transactional systems. Transactional systems that require frequent updates, deletes, etc should use a different solution.

Netezza does not perform well with a significant volume of individual record operations. Netezza is designed specifically for set based operations.

Netezza does not perform well with a significant volume of individual record operations. Netezza is designed specifically for set based operations.

The appliance is installed and maintained by vendor.

• Distributed querying
• Seamless concurrency
• Fast loading
• High velocity analytics

We now have a single store of critical business metrics in the investment bank.

The query optimization is crap, and the machine could use more alerting around bad design and bad queries.

I've been using it for four and a half years.

Releases from IBM are poorly tested, but once they work once, they’re stable – i.e., the machine only goes down immediately after an upgrade.

Scalability is fixed. It’s big, but not at all scalable.

Moderate. IBM is really good at communicating to us that they take our problems seriously, but they don’t seem to fix them very quickly.

We were saddled with this.

The setup was straightforward.

We implemented it in house. My advice would be to follow the tool, and not try to force a schema designed for another system on it.

We have no ROI. We’re a cost center.

No other options were looked at.

It can run heavy CPU queries really fast, and this is valuable.

We have a lot of “campaign” queries that run for our clinical analytical area and this product seems to work well for them.

While some queries do run very fast, you cannot load up the box with several queries.

We've used TwinFin for over four years and Striper for around one-and-a-half.

It does not scale like other databases and expect them to run at the same time.

Netezza does not scale like other databases, so it cannot run several queries at once.

It's good.

It was pretty straightforward, but we had to get several areas involved in initial setup.

We worked with the vendor to implement it.

It is a pretty expensive solution, but it is worth it for the right environment.

With a field-programmable gate array, it has the capabilities to do arithmetic calculations at memory level. Also, the cost-based analysis of query by optimization, it makes query execution faster and provides enough scope to DBA to improve queries.

In my opinion the product is the best for the purpose it has been built.

I've used it for six years.

Not much, IBM guys are quite professional and ready to help with every bit and piece.

Not much, IBM guys are quite professional and ready to help with every bit and piece.

Not much, IBM guys are quite professional and ready to help with every bit and piece.

The level of customer service is good.

The level of technical support is good.

I've never used any other solutions.

Initial setup is pretty straightforward, as IBM provides ramp-up training through in-house training and assigns a technical account manager to make faster resolution of queries.

Both ways, as the box got setup by us and IBM provided a huge set of documents, which made life easier.

Before buying the physical product from IBM, there is an option to use the solution in the cloud to perform a POC and get your stats ready with actual data for better analysis of your investment.

Personally, I like the Compression and Partitioning features.

It has the capacity to handle terabytes of data with query response times that are very low. This has helped us a lot.

It’s a good product for analytical processing, but they need to conduct more seminars and hands-on training and events. They need to be showcasing the product and features to create awareness among businesses.

I have been working on it for the last two-and-a-half years and now we are in process of a tech refresh. We’re moving from the old Netezza to the newer IBM Pure Data Analytics, using a quarter of the rack for Pure Data.

No issues encountered with deployment.

No issues encountered with stability.

No issues encountered with scalability.

They're very good, helpful, and knowledgeable.

It’s a complex setup.

It was handled by the vendor as it's proprietary.

It's fit for the purpose it's designed for. It's an analytical/hierarchical database, now in great demand, that can store plenty of data and return the results in no time for complex queries.

1. Performance
2. Not complex to administer

It provides a key repository for risk information - suitable due to volume of data.

Bitemporal support is needed.

I've used it for three years.

We found some bugs - boundary conditions mostly.

There are no issues with scalability.

9/10 - I have always be able to reach someone at IBM with the correct answer.

Non analytic databases used to be all there was. Netezza provides outstanding performance for structured data.

I didn't set up but our database administrators have said it is much simpler than Oracle, or DB2.In house - have a person trained on PureData - it will pay off

In house - have a person trained on Pure Data - it will pay off

I can't quantify ROI.

Licensing is straightforward - you end up buying the box with Netezza on it as it's an appliance.

Every query has to be set based - no iteration over a result set. stored procedures should be used sparingly.

• Scalability
• User friendly
• Always innovative

Billions of data are processed within an optimal amount of time, and it supports almost real-time analytics. This helps the executives to define their strategy for further expansion and identify potential opportunities with informed decisions.

It has already integrated with Big Data Hadoop; however, integration with XML is still not there for nzload utility.If nzlad supports XML files along with flat flies ,it will give them an edge over other MPP Architecture.

I've used it for eight years.

No issues encountered.

No issues encountered.

No issues encountered.

It's the best.

We used other MPP architecture solutions such as Microsoft PDW and Teradata. However, Netezza has an edge as it is convenient to use and it doesn't need a database administrator to perform a successful implementation of a Netezza migration from any RDBMS.

The initial setup is straightforward as it is an appliance. IBM's technical support team takes care of the entire setup process, and you don't need an expert in Netezza to perform the implementation.

We did it in-collaboration with IBM, and in my opinion, this is the best way to embrace new technology. Once you gradually build up your capability in new technology, you should then take control of it with your in-house talented experts.

We had a significant ROI as business increased multi-fold with such a scalable solution.

Compared to other MPP's, Netezza's pricing is quite reasonable considering long term business expansion with low maintenance cost.

Any potential customer who has an inclination towards large scale analytics, should consider Netezza as an option. This not only gives a faster response, but you can also save on resource cost compared to other MPP's. Netezza's maintenance cost is quite low and this will give you an edge for long term revenue growth.

• The ability to load data very quickly
• SQL is 100% ANSI compliant
• Queries run very fast and require no hints (Oracle)
• No space management
• Tuning SQL is generally pretty easy

For every organization that I have been in that has Netezza, the ability to load and run queries is greatly simplified and A LOT faster than any other DBMS out there.

Netezza is just starting on real time integration with Big Insights (big data). Support for interfaces has been poor. Hoping this improves.

I've used it for nine years.

No issues encountered.

Netezza servers used to have disk issues in the early days, however, for the most part this has been addressed.

No issues encountered.

9/10.

9/10.

I have used Oracle and Teradata as a DBA. I have found Netezza to be the easiest in terms of DBA management

Very straightforward. Data movement is very easy. It works better if you do 1 large file as opposed to several small files

Netezza servers are installed by IBM but implementations are sometimes handled in house and for others it maybe a mixture with BI vendors. We are a BI vendor and do implementations.

Most shops I am in have used Oracle, Sql Server, or Teradata. Depending on what the data is being used for (OLTP, OLAP). OLAP is the best application for a Netezza server.

Cross-database writing and more UDFs.

Netezza NPS 7.1 has added a feature of SET CATALOG statement inside an AUTOCOMMIT ON block which enables a user to do a cross-database writing in a stored procedure (or on a tool "Aginity") which was never done before.

This also allows users to run GROOM, GENERATE STATISTICS etc. in the block as a single execution (auto commit).

Simplified development process with less administration

• Zonemap features
• AMPP (SMP+MPP ) architecture
• High availability
• Field-Programmable Gate Arrays (FPGAs)

The Netezza deployment is easy, and there is less administration and coding than in other databases.

• Correlated queries are not supported.
• Concurrency - the performance dips with number of concurrent queries; for example, if more than 48 queries are run concurrently, it queues up.
• Scalability - if the data increases, you need to go for a bigger appliance as you cannot add to Netezza incrementally.

I've used it for two-and-a-half years.

Some minor SPU communication issues with IP protocol.

No issues encountered.

No issues encountered.

They deliver the products to customers faster and with greater accuracy, i.e. within the agreed-upon due date.

Netezza already had a excellent customer satisfaction and the rating would be 8/10.

We previously used Oracle then migrated to Netezza because its deployment is easy, and there is less administration and coding when compared to Oracle. Also, the query performance is excellent in Netezza.

It is very straightforward because Netezza's initial setup took less than two days and the entire data set was loaded onto the Netezza appliance to which users had full access to the system.

Netezza is an easy-to-use data warehouse appliance. It's extremely fast with a low cost and the customers run their BI and advanced analytics in a very flexible manner.

We also looked at Teradata.

Netezza should have enough advantages with implementation, i.e time to deployment, price, performance, and the ability to integrate with the existing environment.

• Performance
• Simplicity
• Few things to worry about

Netezza technology has served us perfectly well. It is the server for our all BI data.

Our overall business intelligence has improved.

No issues encountered.

No issues encountered.

No issues encountered.

8/10.

8/10.

No previous solution was used.

It was straightforward.

It was done by an in-house team with assistance from some IBM consultants who had very good knowledge about Netezza.

Very good. Our BI enviroment with Netezza, Cognos and Data Stage has been a great success

The in-house team and IBM consultants suggested the solution. There is a partnership between IBM and our corporation.

It is a very good product. Like always, good people with good expertise will help a lot