Netezza Analytics Reviews

The primary use case of this solution is for creating reports from the data in our data mart.

The most valuable feature is the performance.

There is less administrative work and you won't need more than one or two administrators.

Upgrading is very good, the IBM support is very good, migration, and the migration commands are also very good and easy.

Concurrency was an issue. If you run small querries it runs well, and the performance is good. However, when you run multiple long querries or multiple joins, it has some concurrency issues, except for some date covers and some configuration requirements.

Scalability can be improved. When I say that I can add new nodes to the system, compared to other systems, you have to come up with a new box, and not everybody likes that.

In the next release, I would like to see the scalability and concurrency issues resolved. Also, the joining rate features against the swap phase issues need to be addressed.

In regards to the swap phase, if you have less cred then your swaps go down, and your system gets restarted every time, which affects the query files. It should not get restarted. Swap memory issues should be improved.

The Analytics feature should be simplified. Everyone is talking about machine learning aspects and people go for the data mart appliance. The portfolio is built for the data storage and the data is accessed frequently. People would like it to be easier.

I have been using Netezza Analytics for more than six years.

This solution is stable. It requires fewer systems and maintenance.

If you are a controlled business user, it is very stable.

This solution is scalable but it needs to be improved.

We have forty users and we don't plan to increase usage at this time.

The technical support is very good and I am satisfied with them.

The deployment took over one month to complete. We ordered several servers and had to wait for delivery.

I don't think that it is currently available on the cloud, except for IBM Bluemix. They will come up with DB2 Analytics. IBM will come up with a new name.

Moving the data from one box to another box or moving it to the cloud or any other storage, the connectors are there but the efficiency in the movement or the data movement features is similar to USB.

Netezza has already changed its name, so they are no longer selling this solution under this brand. They are selling Neteeza Mako and I would recommend it, although I am still looking for an analytics solution.

Netezza has already launched the new DB2 analytics.

You want to think about whether or not you want to purchase it or consider other solutions such as Snowflake, and Redshift.

When we deployed this solution, the FPGA concept was not at all clear until we started using FPGA with SQL performance-tuning that combines the hardware with the software. It's tightly coupled.

I was not aware of the Sqoop connectors to Hadoop that are used to transfer data from databases to Hadoop and vice-versa. We already had Neteeza, so we only had to download Sqoop. There are several SQL analytics. Not everyone is aware that these functions are already built and that there are separate analytics and SQL analytics function libraries available to download for free.

I would rate this solution a seven out of ten.

We're using several databases, about 1000, and we create lots of queries and run them from different places and from different processes. Both for the processing database and analytic database, we're using queries. It's easy to upload and download the data using the cloud or mobile storage architecture on our site. The solution offers very good management.

For me, as an end-user, everything that I do on the solution is simple, clear, and understandable.

The performance level the solution offers is very good.

The Java encoded integrators are good.

I'm not an administrator, so I can't speak to the solution on a deeper level. For me, everything works well.

The solution could implement more reporting tools and networking utilities.

I've been using the solution for six years.

The scalability of the solution seems good. We've been able to move from small to large databases quite easily.

I didn't participate in the installation, but I believe the process is easy. The installation instructions, from what I understand, are easy to follow. Even the integration from another platform, from DB2 and Microsoft SQL, was no problem for us.

For the last two years, we've been using the cloud deployment model. We're an IBM partner.

We're using various types of databases including DB2 and Microsoft SQL.

I'd rate the solution ten out of ten. We had no problem integrating this solution with our legacy platform. 

We primarily use the solution for data mark creation.

The performance of the solution is its most valuable feature. The solution is easy to administer as well. It's very user-friendly. On the technical side, the architecture is simple to understand and you don't need too many administrators to handle the solution.

The hardware has a risk of failure. They need to improve this. It also needs a system re-index.

They should improve their Schema and base it on Snowflake Schema features.

The solution should offer backup and restore options on some features.

The solution has a reasonable amount of stability. I'd rate it as medium stability since the hardware has a risk of failure. 

The scalability is not good. They claim it's scalable but it's not, especially in comparison with other solutions.

The solution offers excellent technical support.

We previously used Mircosoft services such as Teradata. We were using Teradata for our data warehouse. 

The initial setup was straightforward. It's really easy. Deployment for us took about three months. We used about four team members during implementation.

We handled the implementation ourselves.

We did evaluate other options, but in the end, we got a very nice deal from IBM Netezza.

We use the private cloud deployment model.

I would rate the solution six out of ten. 

We use this solution for our data warehouse in an on-premises deployment.

The most valuable features of this solution are robustness and support.

This product is being discontinued from IBM, and I would like to have some kind of upgrade available.

Scalability of this solution is not possible.

I would like to see a better graphical user interface for database management.

This solution is very robust. There are minor issues occasionally, but they roll out patches and upgrades about once every three months.

There is no scalability at all. It is an on-premises solution, and if you want to scale then you have to buy another version.

Indirectly, we have about four hundred users.

Technical support for this solution is very good. It is coming directly from IBM.

Prior to this solution, we were using a Microsoft product. It was not performing well, and not really an adequate solution, which is why we switched.

The initial setup of this solution is very simple.

Three people are suitable for maintenance.

A team from IBM assisted us with the deployment, which took approximately six months. There were five or six people involved. There were two managers and four technicians.

This solution is very expensive. The annual licensing fees are twenty-two percent of the product cost.

Prior to choosing this solution, we evaluated Greenplum and Vertica.

The biggest lesson that I have learned from using this solution is that a lot of evaluation should be done before starting. Also, we needed to put a lot of effort into understanding the different functions that the product offers. This allows you to best leverage the capability of the product.

I would rate this solution a seven out of ten.

Currently, we are using Netezza to the utmost. We first used it for our data warehouse. Then we moved on to doing analytics. Also, we are now doing some packages on it. Currently we are using it for multiple purposes, but, mostly it's used for reporting.

It is a back end for our SSIS, MicroStrategy,, Tableau. All of these are connecting to get the data. To do so we are also using our analytics which is built on the data.

I'm working for a retail client. We have a lot of reports, which are for store managers. The store managers used to get all the reports using the SSIS package, which was built upon our back end and they would have a lot of performance issues. When I say performance issues, in the morning when there are almost 2,000 users trying to connect to the same report, there were a lot of problems because it was a relational database. People were trying to get information out of it and it would break the flow, actually bottleneck the flow. That's why they were getting the impact.

What we did is, we did a PoC and found this client is well built. Because of that, we were able to create a separate layer for reporting. There was a simple requirement for the DBA, where we don't need to build an index or anything like that. Those reports were improved from a couple of hours to minutes. That was the biggest benefit we've had from this appliance.

For me, mainly, it reduces my costs. It's not only the appliance cost. There are also support costs and a maintenance costs. It does reduce the costs very drastically.

Administration of this product is too tough. It's very complex because of the tools which it's missing. We would require better tools for doing administration. For example, if I need to get a permission of a user on a particular object, it is so complex. It's not straightforward. It would not give me a display of that particular element. Basically auditing is tough to do on it. If I don't have a graphical tool, the auditor will ask me thousands of questions.

This is my seventh year.

Stability, no. In production, no. But when we are migrating or we are moving out from one platform to another... but I guess that doesn't count.

It is scalable to multiples of itself. If currently it is 1X, I can go to 3X, 4X, 5X. I cannot go 1.2, 1.5, 1.8. I have to go 1X, 2X, 3X, a whole interval. That is the only catch, otherwise yes, it is scalable.

We were using a different product. We switched it because of the cost of maintenance. We wanted to reduce the cost of maintenance and it helped to drastically reduce it by some 40 to 50%.

I'm not sure what to compare it to. I am a DBA. For me to set it up, it would be a fast setup. If I'm not a DBA, then it would totally take a little bit of time. For someone who is new to Netezza, it's not complex but it requires prerequisite knowledge. That's it.

I would rate the setup as medium complexity, given that we have somebody who knows a little bit of database administration. I would not say the full administration. I would rate setup around two and a half out of five.

We did. We were actually looking at Teradata and Exadata and we chose Netezza.

The first thing is, do a full PoC where you actually plug in dummy data. Start with millions of records and try out the options which you have already in your environment and see if you really get a benefit in terms of performance. Because this product is mainly to improve the performance.

There are two things. First, it improves the performance and then it's easy to maintain. When I say easy, you would not need a DBA at all. Anybody who has really good knowledge in SQL should be able to maintain this product. That cost, of a DBA, you will completely be eliminating.

The first part of this product is basically performance. If you are moving on from an ODBC database to this, then you would need to do a round of testing on data because you are actually moving from a different technology, that is, to an appliance technology. There are multiple things which can stop you, things you might not be able to do; operations, like booking of a ticket or reloading a feed. We tried to do those things here, in Oracle or MySQL, but when it comes to reporting, this is the best solution we have so far. By that I mean, cheapest and the best.

Then, try to figure out if you really require a code change, because there is a minimal time for a code change; but if it's a request then you should catch it when you're doing a PoC.

Take out any complex situation, give it to the vendor, IBM. Tell them to do a small PoC on the dummy data and let them come up with the performance, then you can compare with your feeds.

Overall, it has good connectivity with almost all the niche technologies we have on the market right now. It can scale up to any technology, any content. That is another benefit of having this.

IBM is a good company which always tries to be competitive with other technologies on the market. If we are stuck, we are trying to purchase something for our content and we are stuck somewhere, something is missing, we approach them and these guys will give us the solution in terms of a patch or an API or something like that, which will help us connect to the newest technologies.

• Its ability to process and query large amounts of structured data.
• Low administrative support in terms of query optimization and indexing support. Indexing and data partitioning is built into the firmware.
• Data compression. It was relatively impressive. I think at some point we were getting 4:1 compression if not more.

I can't because we're using it in a fashion such that a traditional RDMS could have been used in place of it. Our data was relatively small so we didn't see a huge benefit in transitioning new subject areas into production.

Community support. There was none, or very little, especially when using add-on software (e.g. building functions, MapReduce, R, Lua, etc.).

Driver support for windows based applications.

Disaster recovery support. Because it was an appliance, and if you wanted to support disaster recovery, you needed to buy two.

Data center moves. The TwinFin was cool to look at, but moving was a huge orchestration. I would definitely go cloud if I was to choose something with this type of processing power.

Four years.

Yes, with drivers, either OLE DB or ODBC connectivity. Poor backwards compatibility and performance issues with subscribing applications, including MicroStrategy.

No, we didn't have enough data to really press it. The TF-6 at the time could support towards 64TB. We were using 10TB. When running queries natively, it processed most large data queries quickly.

Netezza promoted MapReduce functionality as add-on software, but I thought the support for it was very poor. I wasn't aware of any community that was able to get that up and running.

• Speed
• storage
• RAM

all of which contribute to large capacity.

Faster data processing compared to commodity servers.

In-DB processing with SAS Analytics, since this is supposed to be an analytics server so the expectation is there.

Three-plus years.

No.

No.

Eight out of 10.

Unix, commodity server. Switched to check this technology.

SAS server (Unix) and data storage only.

Expensive to maintain compared to other solutions.

Teradata and Greenplum.

Make sure to check the capability regarding in-DB processing with the application you will be using with this appliance. I am using SAS and it's a dis-appointment due to limited in-DB processing, including data connection pool, that was never resolved by both SAS and IBM Netezza.

There is minimal on-going maintenance.

There were some reports we couldn't get because of performance, but with Netezza we could get more of them.

It needs a better in-house development tool.

I've used it for three years.

Functions are difficult to deploy.

No issues encountered.

No issues encountered.

7/10.

7/10.

Our customers mostly switch from traditional RDMs to appliances.

It is very easy to setup.

We used an in-house vendor who were 8/10.

Choose your most complex scenario. Do a POC and try to scale.

You should know how it works well so you can use its power. So, start with a partner or vendor team.

ARULES() function is the fastest implementation of the associations algorithm (a priori or tree) I have worked with. In comparison with the R associations package, it is +1000x faster. The issue with the R implementation, and R in general, is that the functions do not work on large sets of data. R would generate a 100,000 x 100,000 element matrix for some of the arules runs we do – very, very inefficient programming.

Any in db machine, learning functions help by eliminating the data transport issue. NZA goes one better by allowing you to utilize a tuned engine (software + hardware) to run the functions. The result is that we can run algorithms that would be impossible to run on other platforms.

We are using an older version. Some improvements are already implemented, such as the addition of neural networks. Other improvement would be to make the existing algorithms even faster, e.g. kmeans can actually be parallelized. If this reworking of the algorithm is done, it should leverage the MPP architecture of Netzza and run much faster.

Also, some algorithms are faster than almost any other method or system e.g. NZA.ARULES() function. Whereas others are not as fast and could probably be optimized for an MPP architecture like kmeans function.

2-3 years on and off. 1 year for actual integration into another tool for mass consumption.

For deployment, ensure you follow the instructions. The version of Netezza must be matched with the version of NZA. We tried to install a newer version of NZA not supported by the version of Netezza we had and it did not work.

N/A. We did not engage IBM tech support, mainly due to past experiences where it is faster, easier and much less stressful to just figure things out yourself.

Rapidminer, R, DB2 intelligent miner, SSAS data mining were all tested for association rules. Rapidminer and R did not pass. They use matrix math, and cause +100x performance degradations. DB2 intelligent miner, SSAS data mining, and likely also NZA follows the original a prori methods of using sets, not matrices.

DBA set it up, but it seemed very simple. I helped with designing the overall architecture. If you stick with NZA as a “function repository DB” concept and do not put data on it (as recommended in the install manual) you will be ok.

In-house. Don’t over think it. Just apply some base architectural principals and give it a try. If you find something not working make adjustments.

I had nNo visibility to pricing. Netezza in general though, is very cost effective. If you compare to other MPP platforms like Hadoop. Hadoop requires a very “non-enterprise” culture to implement and a team of designers / engineers. Netezza requires maybe 1-2 admins.

I would have to understand the specifics of the organization, the data size, the tasks, etc. to make any recommendations.

Its query performance and speed.

Earlier there was high latency to query extraction but Netezza has improved the speed for all OLAP operations. This has helped the organization to get the business answers right on time.

• Matching up with big data.
• Netezza has been built only for OLAP and structured data, and I think IBM must do something to match it to Hadoop scalability.

I've used it for four years.

There’s only been one, where data slices were corrupted soon after the deployment but IBM has fixed it in a perfect manner.

No issues encountered.

We didn’t have many scalability issues, except when it touches the PB storage data and we need to move it to external storage. Netezzas’ highest model storage capacity is 1.2 PB.

Great, 8/10.

Great, 8/10.

We have previously used Microsoft SQL server, but we switched because our business wants fast and reliable appliance like Netezza. Although MS SQL server is reliable but Netezza is known for it's MPP and performance when compared to other RDBMS appliances.

Straightforward.

An IBM team deployed it for us, and they were 9/10.

Business questions are answered much quicker than what we use to do it earlier.

The Netezza appliance is bit costly for a mid-sized organization but highly effective on the performance side and for structured data.

We also looked at Oracle and SQL Server.

I don’t want to be biased but it all depends on the business requirement because there are many models for it, which range from 7.8 TB to 1.2 PB (uncompressed). If the business has done a feasibility check on Netezza for their scalability plus the growth and they found it to be within their estimates then I would suggest that they have taken off from the right runway.