Teradata Reviews

We primarily use the solution for data warehousing.

The loading time of the solution is quite good.

What really impressed me is their approach to design the data warehouse. It's very different from other solutions. They have their own methodologies for doing things, and they can come up with a very solid and good design that can stand the test of time.

The functionality of the solution is excellent.

The solution can scale.

It's quite a stable product.

On the product side, I don't think anyone can actually beat them with data warehousing.

I'm not sure about the unstructured data management capabilities. It could be improved.

They should, I think, try to do more of this open-source initiative to encourage more people to use it. Otherwise, it's my opinion that they might lose our business in the long run.

I've been using the solution for about three years at this point.

As one of the top companies in the world, the solution is very stable. There aren't bugs or glitches. It doesn't crash or freeze. It's quite good.

Product-wise the scalability and usability, is all excellent. They are the top players in this with their new database. The cloud helps make it so scalable. We're catching up and starting to scale, however, we aren't there yet.

I don't recall if the solution had a complex or straightforward setup. I wasn't part of the process.

I'm not sure if we would want to keep paying for the solution. They should make some of the software a community edition or something like that to encourage more people to use it.

This is a very good solution. 

After looking at the recent price drops, they need to offer very good discounts for people that bought it. The value proposition is actually quite good compared to many years ago. For most of the enterprises out there, they're focusing mainly on structure data. This solution ticks that box.

As long as they can control the price incrementally in the future, I think they're a very good strong platform.

I'd rate this product in terms of its functionality, stability, and scalability, as almost perfect. It's a nine out of ten. I don't think there's anything to complain about. It's only the price that's a sticking point for us.

Each has its strengths and weaknesses; this is why we use a blended environment. We have a holistic view which is very mature and thus, it is impossible to give a concise answer.

However, converting the Teradata from a pure BI to an ODS has been our greatest achievement; it effectively has allowed us to remove over 20 portion copies of the data sets on other DB platforms for real-time operational reporting purposes.

It is the core of our fundamental real-time reporting and operational planning. It has saved us over eight figures in the operational run costs, improved data quality and consistency as well as reduced our overall infrastructure support requirements.

The increasing volumes of data demand more and more performance. I truly believe that in five years, we will breach the effective limits of Teradata to perform in a multi-petabyte environment, i.e., without significant changes to its underlying architecture. If this occurs, we will be forced to migrate to a more traditional platform (such as IBM Informix).

We have aggressively been using BI for over 20 years, with this evolving environment. Our most recent setup was about three years ago.

We have a broad range of BI and reporting tools, built on top of the Teradata Platform. It, currently, is the active Data Warehouse on 12.x , although we are migrating to 13.x after the New Year. This is supported by our IBM Congos (12), MicroStrategy (10) and the QlikView (12) reporting tools. We have also built extensive analytics on a Java base as well as some Microsoft BI integration.

We have had stability issues quite frequently, but this is mostly with the Cognos environment, as it is growing beyond its limits in terms of the active user access. This is why we are considering migrating significant portions of our over 4000 users to a coded environment in place of the platform.

Again as mentioned before, there were scalability issues in regards to Cognos and the over 4000 users in a single active environment.

Our in-house team is world-class, so we are not reliant on any external support.

We have moved from a distributed heterogeneous to a centralized homogeneous environment. Costs, data quality, sharing of information, and supportability were the reasons as to why we switched over to Teradata.

The setup took place too long ago to remember.

Negotiate, negotiate, and negotiate some more. But long before you start to have a clear understanding of your direction, use patterns and check the roles that BI plays in the organization. Make sure you have the in-house skills to design and support the solution, as relying on external sources is extremely costly and tends to lock you into specific platforms, tools, and paradigms.

We did a six-month review of potential candidates and options. Every three to five years, we re-evaluate the selection criteria and re-open the solution's design with an invitation to the vendors to offer an alternative. The process consumes about three months, but it has allowed us to keep current and, more importantly, to leverage off the process so as to ensure that we are getting the best value for our money.

This comes back to understanding the what, why, and how of the solution. Once you understand that, then plan it accordingly and ensure you have sufficient time to address any of the surprises that could occur.

Each tool fills a niche and is used accordingly. I doubt if there is anything perfect out there, as each tool has its own considerations when being deployed.

Our greatest concern with Teradata is the performance impact of the OUTER RIGHT JOINS across a petabyte environment.

We use Teradata in our data warehouse and we extract data. We have a data department that uses many tools for data extractions.

Teradata has good performance, the response times are very fast. Overall the solution is easy to use. When we do the transformation, we have all of our staging and aggregation data available. 

Teradata could improve by providing better training. For example, Oracle provides good overall training. It is not easy to find information on the internet.

I have been using Teradata for approximately eight years.

The solution is stable. However, there are times when we are using large amounts of data and we can see some latency issues.

Teradata is scalable. We have two large servers and if we need to add new servers it can be done. Additionally, adding hard drive space or more performance is not a problem.

We have approximately 15 users using this solution in my organization.

The technical support is good but they could improve because sometimes they can take two weeks to resolve issues.

The implementation took approximately one month.

We did the implementation of Teradata using their support.

The price of the solution could be reduced, it is expensive.

I would recommend this solution to others.

I rate Teradata a nine out of ten.

The two types of partitioning have been very significant for us - row and columnar partitioning.

With the current machine we are able to eliminate the use of OLAP cubes and allow customer queries to run directly on the Teradata machine.

We have now started running more profit generating activities on the Teradata machine, as opposed to just running reports, as in the past.

Data synchronization to the DR site.

My company’s management has to decide whether to invest in this area. This is more an internal issue at the company and definitely not a problem with the Teradata product. If we end up migrating to another platform, this will be the reason.

We have been using the solution for seven years.

Teradata is the most stable platform that I’ve worked with in my 20-year career.

Teradata’s scalability is excellent.

Teradata’s technical support is excellent. The support people are highly professional, and nice, to boot.

My previous background was with Oracle. I changed jobs and was asked to handle the Teradata team. It was a chance to learn something new and interesting.

Initial setup is quite straightforward, but previous experience with other databases tends to make it more difficult, because it takes a while until you get used to thinking in Teradata terms, rather than Oracle/SQL Server/PostgreSQL terms.

It’s a different animal. However, once you start thinking like a Teradata DBA, things are much easier.

Pricing can seem high, but when all factors are taken into account, the total costs are comparable to other databases as:

• Few DBA’s are required
• Unplanned downtime is very rare.

By avoiding the Enterprise solutions, you can actually end up with a cheaper, yet much more powerful machine. We moved from an Enterprise platform, to non-Enterprise and ended up with a machine that was 20X more powerful. We got an amazing performance boost.

Every few years we examine the option of migrating to other platforms such as HPE Vertica, Oracle Exadata, or SQream.

In the past, it turned out that other solutions, in order to provide the full range of abilities that the Teradata platform provides plus the migration costs, would end up costing more than Teradata does.

Make sure that you have a good Teradata DBA to help implement the solution. A great Oracle DBA is not sufficient, because it takes a while to internalize that they are two different things.

Make sure that you have a good backup/recovery/DR plan, and that it is covered by the infrastructure you are purchasing. Otherwise, you might find yourself with a system that performs great, but has no good DR solution.

My current use case is an analytical system for an oil and gas company. They have a data lake and they are getting their data from different IoTs and different SAP systems. They wanted to have some feedback about their system and check on their production.

The IoT center's data was actually our use case, then how we can use that data to prevent disaster from happening. Previously, this work was all done manually. If there is a leak in the pipes then it is a large area to search because there are hundreds of kilometers that have been run.

To tackle this problem, they use IoT sensor data. It helps them to understand how the flow is working at a specific point in time, what happens when they're drilling the oil and other types of data. To complete the analysis, we use an analytical system or a Teradata Azure system that we designed.

The ECL was designed in a manner where we were doing the transformation on Hadoop. It is more like a balanced system where you use Hadoop for what it is good for, and where you use Teradata for its purpose.

I have worked in several different environments. The largest Teradata implementation on Azure was done by me. Right now, I'm working with AWS but previously, I have implemented both on-premises and hybrid deployments.

Performance-wise, Teradata beats everything.

The flexibility in design is very good.

When you want to tune it, it is very easy to do. I have worked a lot as a DB and I know that when there is a query that is stuck for hours, and you want to tune it, the task is quite easy. You can use the indexes and architecture, and exploit the power of Teradata.

There are lots of improvements that Teradata is working on and many that have already been done. However, recently I was in a session with people who are working on the data sciences side of the business. The data science group is not using the Teradata modeling features. Rather, they are using third-party tools for the prediction and forecasting models that they are building. Teradata should focus on functionality for building predictive models because, in that regard, it can definitely improve.

In my experience with Teradata, I have seen their sales strategy and that needs to change. As an organization marketing a product, they need to be cloud-focused instead of the on-premises thinking that they currently have.

There are a few things where you are totally dependent on the customer service and support from Teradata. This is an area where they really need to improve a bit, especially when you're talking about cloud service integration. Depending on the environment you may need to contact the AWS team, or the Azure team, or the GCP team, or the Teradata team. In all of these environments, improvements need to be made.

I have been working with Teradata for more than a decade, probably close to 11 years. I have been in the industry for approximately 18 years.

We are satisfied with the stability.

It is quite easy to scale. For a cloud-based deployment, it's even simpler now.

Previously, it was easy if we just wanted to add power but there was an impediment when you had to add a node. Similarly, it was difficult when you had to shift to the newer nodes. Now, however, with the cloud, it's easy to do.

For the on-premises deployment, a lot of people consider the initial setup to be difficult. Keep in mind, however, that Teradata is a million-dollar product, so they set it up for you.

For a cloud-based deployment, it is now pretty simple to deploy.

The price of Teradata is on the higher side, and I think that it where they lose out on some of their business. The price should be reduced to make it more competitive.

One of my clients recently tried to switch solutions but they have rolled back to Teradata. The same thing happened with another company that I know of in Pakistan, where they tried working with an IBM product.

My advice for anybody who is implementing this product is that they really need to hire the right people. Get people who actually have worked on Teradata to guide them.

You can buy Teradata and you can get it up and running, but until you hire a few good people, you are not going to get the full benefits from it. These people are not resources that you would ask Teradata to provide you. Rather, you can hire them from the market.

The important part is that you need to have people who have good experience with Teradata because they can truly exploit its power for you.

Overall, this is a good product. It is close to the best but I cannot rate it perfectly because of the price.

I would rate this solution a nine out of ten.

We used the solution for our data warehouse. 

The availability is very good.

We have found performance to be one of the most valuable aspects. 

The solution scales well on the cloud. 

Teradata is a bit late for the cloud. They maybe need to have some room for cloud improvements.

Scalability is limited on-premises. 

The solution could use more AI support.

I've used the solution for a while. The last time I used it was two months ago.

The performance is great. It's stable and reliable. There are no bugs or glitches. It doesn't crash or freeze. 

Teradata is a 100% stable environment.

In on-premise systems, it was a bit tricky to scale. However, in the cloud, it's very easy.

People are not directly connecting to Teradata. However, they are using reports that are fed from Teradata. In that sense, the entire company is using Teradata. It's more than 1,000 people.

I'm not directly connected with technical support from Teradata. I connect the local support here, and they are connected to Teradata, and on the weekends or after working hours, we get support and solutions. So we were happy with Teradata's and local company's support.

Positive

This product was already set up when I joined the organization. As far as I know, they were trying to replace SAP BW. There was an SAP BW system, and they were trying to replace it with Teradata. 

It was easy for me to set up since I didn't handle the setup. Our local support company managed everything and prepared the environment, and handed it over to us. It was very easy in that sense.

We had a local support organization assist us in the setup.

We have seen an ROI. It's worth the money.

Teradata is not a very cheap solution, yet it is a good solution. You get a good return on what you have paid for.

I'm an end-user.

If new users are experienced database users, they will know the administration side is different than the other databases. However, it's almost the same for an end user, a developer, or somebody doing reports on Teradata on another database. It has some differences, yet the logic is the same.

I'd recommend the solution to others. I love Teradata.

I would rate the solution an eight out of ten.

I was happy to use it. I was glad to have Teradata, since, with Teradata, we can meet the requests of the customers, and it is highly available. 

Primarily, Teradata is a traditional data warehouse, but we also encourage our customers to adapt to the logical data warehouse and data lab.

The most valuable feature is the ability to be anywhere - Teradata can be deployed on-premise, on the cloud, or in a virtual machine, which means customers can move without having to create their architecture all over again.

Teradata's pricing is quite high compared to Redshift, Synapse, or GCP alternatives. In the next release, I would like Teradata to refine their Object Store to be more compatible with cloud environments.

I've been working with Teradata since 2014.

Teradata's stability is very strong, and our customers feel their data is safe with it.

Teradata's scalability is good, it takes only the push of a button to scale up, and if that's not enough, you could scale with the cloud or a virtual machine.

The initial setup is straightforward if you have some knowledge about the logic of the environment. However, for those without knowledge, there will be a learning curve to understand how to use the solution.

Our customers say that Teradata makes them faster, smarter, and capable of more sophisticated analytics.

For anyone thinking of implementing Teradata, I would recommend preparing by understanding the technology and putting in the effort to keep it being adaptive to different and urgent requirements from your business. I would give Teradata a score of ten out of ten.

We use it for enterprise data warehouse (EDW) with on-premise hardware. The company uses EDW for most MIS functions.

It has massive parallel processing ability to do large amounts of concurrent querying. It has given our business the ability to gain insights into the data and create data labs for analysis and PoCs.

Speed of complex queries and the ability to schedule give business users time to analyse data rather than waiting for queries to run.

We are using an older version at the moment. We are looking for a more flexible cost model for the next version that we use, whether it be cloud or on-premise.