Teradata Reviews

My primary use of Teradata is for data warehousing.

Teradata's most valuable feature is that it's easy to use.

Teradata's UI could be more user-friendly.

I've been using Teradata for over five years.

Teradata is pretty stable.

Teradata is scalable.

The initial setup was straightforward.

We used an in-house team.

I would rate Teradata as eight out of ten.

Teradata is used for many use cases, such as clickstream, website support, and manufacturing control.

Teradata has helped our organization accelerate substantially the decision-making that happens.

The most valuable features of Teradata are that it is a massively parallel platform and I can receive a lot of data and get the queries out correctly, especially if it's been appropriately designed. The native features make it very suitable for multiple large data tasks in a structured data environment. Additionally, the automation is very good.

I've been using the same UI for 20 years in Teradata. It could use some updating. Adding more stability around Teradata Studio would be outstanding. Teradata Studio is a Java-based version of their tool. It's much better now, but it still has some room for improvement.

I have been using Teradata for approximately 20 years.

The stability of Teradata is outstanding.

Teradata is highly scalable, it is excellent.

We have approximately hundreds of users using this solution.

I have not used support recently, but I have previously.

I previously used SQL Server.

The initial setup of Teradata is complex. The business layers on top of Teradata add to the complexity. The way the business uses Teradata adds to the complexity that the software itself doesn't necessarily have. 

You can do an upgrade for Teradata in a couple of days. Deploying it is not difficult at all, nor is it time-consuming.

I rate the ease of setup for Teradata a one out of five.

The price of Teradata is expensive. However, what they deliver they are outstanding. If you're looking for an inexpensive solution to run a database, this isn't your tool. It's the Ferrari of databases for data warehousing.

There are add-ons that you can purchase, such as special features. Teradata likes to sell an industry logical data model that's customized for just about every industry they have clients in. That is an extremely expensive add-on, but it does give you a step up in getting your logical modeling created. They've also done some work towards being able to go from logical to physical in an automated fashion with that ILM.

Teradata is being used on-premise, but we're moving to the cloud and I don't know that we'll retain Teradata further. We might be switching to the Google platform and their native databases.

Make sure that your data volumes are large enough for it and that you follow their standards. The modeling for Teradata is slightly different than anything else out there. Match your primary indexes if you can. These PI-to-PI joins are incredibly fast, even with massive amounts of data. I've worked on Teradata installations in the petabyte range.

I rate Teradata a nine out of ten.

Teradata was mostly a control system for us where we were fetching the data from it on basic time intervals, on various DVs and various schema where we had to fetch the data. Reading was the main operation that we used Teradata for, but while reading, there were complex ENTs that we had to write because of a few data that was supposed to be transformed and then fetched, so that was the major use case for the solution.

There are several features of Teradata that I like. One of the most basic is the indexes. I also like that it provides lower TCO. It also has the optimizer feature which is a good feature and isn't found in other legacy systems. Parallelism is also another feature I like in Teradata because when you are running or hosting on multiple systems, you have this shared-nothing architecture that helps. Loading and unloading in Teradata are also really helpful compared to other systems.

Teradata is good, but eventually, my company is moving to a higher-level system. You wouldn't want to work on a lower-level system.

As for the areas for improvement in Teradata, since I was working on the very basic, legacy systems, the memory thing was always a challenge. If Teradata is moving to the cloud, the space constraint or the memory issue that my company generally faces will eventually resolve, in time.

What I'd like to see in the next release of Teradata is that it becomes full-fledged on the cloud, apart from better connectivity to various systems. For example, if I have to read or include a Python script, if I write some basic codes, I should be able to read even unstructured data. I know that it's not supported even in Snowflake, but at least semi-structured data support, if that can be a little more enhanced, that would be good.

I've been using Teradata for a year and a half now, and I'm using its latest version.

In terms of stability, Teradata is stable. All legacy systems are quite stable and do not have that much downtime, probably because no one would work with a system that is not stable.

Teradata is scalable, but it takes time because you have to increase the servers. On the legacy system, it's the physical servers that you increase and that takes time.

I don't have experience with Teradata technical support, because the client handles the maintenance. It's the client who reaches out to the technical support team in case there's a need to increase service on the Teradata system, or if there's any downtime or any glitches in terms of catching or loading the data, but that doesn't happen often.

Setting up Teradata took time. The server has to be set up and that takes time. Next, the IDs need to be set up and the role level security that the legacy system provides is definitely not up to the mark when compared to the cloud, so that is a concern. I'm talking truly about the legacy system. I haven't worked on the cloud part of it. It took more time to deploy Teradata.

Deploying the solution from dev to the QA environment, for example, creating tables, then copying over the data, are completed within twenty four to forty eight hours. It's the timeframe the DBA used to give, which is pretty high. With the closing features that we have normally, that would be a long time.

Implementation was taken care of by the client.

Teradata pricing is fine, and it's competitive with all the legacy models. On a scale of one to five, with one being the worst and five being the best, I'm giving Teradata a three, because it can be a little expensive, when compared to other solutions.

Teradata requires maintenance, but the team in charge of the maintenance was not in-house. It was taken care of by an external support team. There are forty to fifty users of the solution in the company. I'm use Teradata on a daily basis.

I'm rating Teradata an eight out of ten.

The most valuable features are the large volume of data and the structuring of the data to optimize it and get very optimal data warehouse solutions for customers.

An area that needs improvement is the cloud-based version of the solution because it's designed for on-prem and then transferred to the cloud version. Teradata needs to pay attention to the cloud-based solution to make sure it runs smoothly. In the next release, I would like Teradata to be cloud-agnostic in order to not limit customers' choices.

I've been using this solution for fifteen to twenty years.

Teradata is superior, stable, and has no problems.

Teradata is easily scalable. 

The setup is complex and requires specialized people for implementation.

The cost of running Teradata is quite high, but you get a good return on investment.

I've also evaluated Snowflake, which allows you to expose your data to multiple sources for monitoring without additional work.

For the on-prem solution, there isn't really anyone who can compete with Teradata. I would rate it as eight out of ten.

Teradata Data Lab is used for simulations.

In Data Lab, you can schedule any testing you want to do in production. You can take a small subset of data from production, copy it there, and run all your tests. It reduces your testing costs because it's all in the lab.

If I want to implement an upgrade, I'd like to see how it will be different. Ideally, Data Lab should help me test production items and also do future things. Future releases should be downloadable and testable in Data Lab.

Data Lab is very stable. It has been in the market for 25 years.

Data Lab is highly scalable. My organization has a lot of users, but each company has more than 30,000 users. More than a thousand customers are using it, so there are more than 300,000 users out there.

Teradata technical support is excellent. 

You don't have to do any installation. It is an out-of-the-box solution. It's low maintenance. We have one person, but if you need 24/7 coverage, you need four or five people. 

We have a subscription. Nowadays, everything is cloud-based, so you pay for the subscription, and it is pretty affordable. There aren't any additional costs. So what you see is what you get. 

I rate Teradata Data Lab nine out of 10. 

We primarily use the solution for data warehousing. 

Primarily what happens is, in Juniper, they have internal business analytics and intelligence, a business intelligence analytics dashboard, and a lot of databases that capture the customer feedback. 

It actually captures all the internal defects that are tracked on products. There are different databases that accumulate all this data. Basically, you need to be able to source the data and do some filtering. We extract, transform, and load logic. We have to run certain business rules based on what the program or management team looks at. The teams want to filter out some of these problems that they have, and they want to analyze how well the company is responding to many of these customer issues, et cetera.

Our company is a large company with each particular team using its own database and its own database tables. It becomes extremely hard for the company to take the data from different data sources and be able to correlate everything and be able to analyze many of the processes that are happening within. There is a workflow discontinuity that has been observed due to the fact that the data is distributed. In order to understand exactly how a request comes in from the customer and what goes on behind the scenes in order to resolve the problem or to be able to provide the support to the customer, and how long does it take before the problem gets fixed and delivered, et cetera, we need to centralize everything and we use data warehousing for that. 

There are other similar kinds of business rules filtering that happen on the dashboard as well. This enables people to be able to view the data that is needed and the metrics that are of interest to them and is especially useful when it comes to the executive team.

The most valuable feature is the ability to be able to access the different data anywhere, and the Cloud Data Warehouse solution enables that. 

To be able to extract, transform, and load logic, and also to be able to correlate the data in different databases and not just correlate it in one is great. 

If I want to be able to perform certain database queries on a joint operation between database tables located on two different database sources, et cetera, I can do that. 

The most important thing we get out of the product is the intelligence that we derive. How the company feels in terms of process efficiencies is positive. In order to understand how a workflow is actually executed within the company, we need the assistance of this product. That's where the maximum value comes from. 

The ability to access the data from a website or from anywhere is very important. The people themselves can also be anywhere. 

The licensing system enables the company to track how a switch is used by an end customer, an end-user, and what different features the customer is actually running. It tells us a lot about the product. You have a lot of quantitative data that can provide an understanding of people's behavioral patterns and people's usage patterns when it comes to understanding what features or what are those elements that customers are most interested in - that can be tracked. 

The solution is stable. The product is reliable.

The scalability is good. 

Technical support has been good. They are helpful.

In terms of improvements, I can only speak from the dashboard perspective. 

The most important thing is that I don't know how far the dashboard integration goes. People, for example, were using the Cloud Data Warehousing product, however, they were actually building their own dashboards, et cetera. That's like double the amount of work. The company should have the ability to integrate with something like Tableau to make everything more standardized.  

With the customer data, we were able to integrate very successfully with Tableau and we were able to use it well from an end-user perspective. We were using the Tableau interface for understanding what our customer buys, et cetera. For example, for the customer financial data aspect of it, the business data, we were able to use Tableau dashboards. It would be better to use back-end data warehousing and also have dashboard reporting and have everything integrated properly. It doesn't need to be Tableau. It can be some other dashboard. However, it needs to be standardized. 

The usability could be a bit better. It could be a bit more user-friendly.

I've been using the solution for five or six years or so. We've used it for a while. 

The solution does seem to be a quite stable solution. We haven't had any major issues that I am aware of. Generally, stability has never been a problem with the product. There are no bugs or glitches. It doesn't crash or freeze. 

The scalability seems to be pretty good. If a company needs to expand it, it can do so.

Technical support is decent. We are satisfied with the level of support we receive. 

Some time ago, we also implemented SAP internally within the organization. For some reason, there was a decision not to go with the SAP HANA. I don't know why that decision was taken. Likely, it had to do with the kind of data or the kind of use case that we had and the data sources that we had. Teradata was considered to offer better performance and was a better-performing product.

Teradata definitely does what it says, in terms of an on-demand platform, as it's a cloud service and it is definitely scalable. It's secure and it does provide scope for a lot of automation. The provisioning part of it, the administration and backup recovery as well as the analytics are some things that could be integrated in a more advanced manner. Maybe certain enterprise use cases need to be included so that users in an enterprise environment can build an analytics dashboard out of it. Support is good, however, the support requirements are not too much. Overall, the usability can be a little simpler. In general, we've been satisfied with it as a product.

I would rate the product at an eight out of ten. I want to be a little bit conservative in my rating as I want to be sensitive to the fact that people really want to be able to do the slicing and dicing of data at a user interface level and to be able to see all the insights at once. At that level of usability, to be able to slice and dice, you need to give a dashboard to a user. 

If, for example, I have a certain type of organization that has a hierarchical organizational setup, I should be able to slice it to a specific group or a specific department, or a specific team. I should be able to see the metrics corresponding to that, or corresponding to the drilled-down data. While that's possible today, what I'm trying to say is that to be able to do it as a business user, to be able to use an interface in order to be able to do that kind of custom slice and dice operation and see the data in real-time, people are looking for more. Users want a level of usability from a business rules perspective, et cetera. That's something that people are looking forward to from intelligent and smart dashboards. It just needs to offer something that is much closer to capturing real-time information.

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 use it as a data warehouse.

I like this solution's ease of design and the fact that its performance is quite good. It is stable as well.

The scalability could be better. The on-premises solution is always more complicated to scale.

The flexibility could be improved. The product is good if you know what you're planning to do. If you're designing as well, upfront, then it's fine. However, if you've made a mistake in the design work or your system, then it could be quite complex and expensive, and it may not preform well.

I've been using Teradata for around four years.

Teradata is a stable solution.

I've worked on the on-premises solution, and it is always more complicated to scale. We currently have hundreds of users.

We used Oracle Database before Teradata.

Teradata is quite a specific tool, so if you have suitable use cases, then I would recommend it. On a scale from one to ten, I would rate this tool at seven.

I mainly used Teradata as an EDW and for customizing and integrating CLDM, applying aggregation in the database, and analysis.

Teradata's best feature is its speed with historical data.

Teradata's UI could be improved.

I've been using Teradata for about four years.

Teradata's stability is good.

Teradata's scalability is one of its best features.

Teradata's licensing is on the expensive side.

I would rate Teradata nine out of ten.

The purpose that we are using Teradata for is to migrate data to the cloud.

The most valuable feature of Teradata is security. It runs on Unix and Linux platforms which provide better security.

Teradata could improve by being less complicated. There are some aspects that are not available on the Unix server and a Unix system is required to access some data, such as in case of an emergency.

I have been using Teradata for approximately one year.

Teradata is stable.

I rate the stability of Teradata a seven out of ten.

We have more than 1,000 people using Teradata in my company.

I have not used the support from Teradata.

The initial setup of Teradata is not simple.

We have different teams of approximately 200 people total that are supporting Teradata in many cities and branches.

The price of Teradata could be less expensive.

I rate the price of Teradata a seven out of ten.

We did not evaluate other vendors before choosing Teradata.

I rate Teradata an eight out of ten.