Teradata Reviews

I use the solution in my company for reporting.

The tool's flexibility and capacity for expansion are areas of concern where improvements are required.

I have been using Teradata for two years. My company is an end user of the product.

It is a stable solution. Stability-wise, I rate the solution a nine out of ten.

In our company, when it comes to Teradata, we have an appliance in place, and we plan to upgrade to another appliance that offers more capacity.

I rate the product's scalability to be below average.

Around 100 people in my company use the tool.

The tool is used daily in my company.

It is difficult to get someone with technical expertise involved with the solution's technical support team. I rate the technical support a four out of ten.

Neutral

I only have experience with Teradata.

I rate the product's initial setup phase as above average on a scale of one to ten, where one is difficult, and ten is easy.

The solution is deployed on an on-premises version.

For installation, my company only used the services offered by Teradata.

I rate the product price a nine on a scale of one to ten, where one is cheap and ten is expensive.

My company has evaluated other options against Teradata, and I see that it has been used in our company for the past four years.

The tool did enhance our company's data warehousing and analytics capabilities.

Teradata was crucial for our company's data analysis, especially for every campaign we run, including the pricing, exercises, and analysis.

Teradata's feature, which had the most significant impact on our company's data management, revolves around the analytics feature it offers.

I rate the tool an eight out of ten.

Our use cases were related to banks and other financial institutions. 

The tool's most valuable feature is the warehousing model. 

Azure Synapse SQL has evolved from a solely dedicated support tool to a data lake. It can store data from multiple systems, not just traditional database management systems. On the other hand, Teradata has limitations in loading flat files or unstructured data directly into its warehouse. In Azure Synapse SQL, we can implement machine learning using Python scripts. Additionally, Azure Synapse SQL offers advanced analytical capabilities compared to Teradata. Teradata is also expensive. 

I have been using the product for three to four years.

I'm working in a very stable environment with Teradata. We have a lot of flexibility, especially in terms of automation.

I haven't contacted the tool's support yet. 

I have used Azure Synapse SQL. Regarding Teradata, I've only explored it for proof of concept purposes. As a gold partner of Microsoft, we recommend Azure Synapse SQL. However, Teradata seems to be the preferred option when handling large transactions over Azure Synapse SQL. While I haven't explored Teradata extensively, based on colleague feedback, it's considered ideal for financial transactions involving millions to billions of records per day. On the other hand, Azure Synapse SQL is more suited for data warehousing and operational reporting.

The tool's deployment is complex. 

The tool costs about 30,000 euros a month, while Azure Synapse SQL only costs 10,000. 

We used Teradata for proof of concept purposes but eventually transitioned to Azure Synapse SQL for managing large data volumes. With Azure Synapse SQL, we could load nearly 130 million records daily from a single data source, and we had eight data sources. This data-loading process took only four hours to complete. It is also based on the .NET framework. 

If you're familiar with SQL, working with Teradata might be considered complex compared to Microsoft SQL or Oracle.

If you want a tool to handle financial transactions and generate simple dashboards, Teradata might be the faster option. However, if you also require machine learning, operational reporting, etc. I would recommend considering alternatives such as Azure Synapse SQL.

I rate the overall product a seven out of ten. 

We use Teradata as our company's data warehouse engine to process tons of data since we are the Central Bank of Columbia, where we use that for statistics to study several areas of banking. Our main database, data warehousing, data mining, and back office statistics are done with the help of Teradata. We heavily use Oracle as our transactional database, but we use Teradata for all other purposes.

I am not exactly the person doing the programming and exploring the product's different features. To get information on the product's features, I will have to contact some engineers in charge of programming. The most valuable feature of the product is the ability of the product to process huge amounts of data without creating conflicts in the queries. The way the database and IntelliFlex are designed, you can process several queries from different applications simultaneously, and they don't conflict with each other. I mean, I think that's the reason why we find improvements in our query time. The way the queries are internally in IntelliFlex process makes them less complicated. In other databases, when you start a query, the dataset is put on hold for a while, so all the queries have to wait for the first query to finish. IntelliFlex and Teradata are designed to avoid such an issue because I am unsure. I feel Teradata IntelliFlex can function in the aforementioned manner since they manage smaller sets of data, because of which there are no conflict queries between one and the other.

I don't have the exact details of the improvement needed in the performance of Teradata IntelliFlex because I work with the infrastructure department. The infrastructure department is in charge of getting infrastructure for the system to work, but before having Teradata, the data processing was taking a lot longer than it is now. We got into Teradata because we needed fast processing of huge amounts of data since, in the past, we were trying to achieve it with Oracle databases, and it wasn't good enough. In the last two years, the processing times have reduced by a third or a fourth of the time without causing any problems because of the efficiency of the Teradata engine.

The only issue our company has with Teradata IntelliFlex is that it is not cost-effective because of the way the product has been designed. We have Teradata IntelliFlex on-premises because we pay for a lot of muscle that we are not using. The problem we're seeing is that when we try to move into Teradata IntelliFlex's cloud services, we notice that Teradata doesn't have a flexible price structure to allow you to use a fraction of IntelliFlex's extension and charge just for the use of the solution. We receive messages from Teradata asking us to pay for the services we use on-premises, while in reality we use less than 30 percent of the machine's capacity.

There is something that is not working in favor of the business models for IntelliFlex when you plan to move to the cloud.

I have been using Teradata IntelliFlex for two years. Our company plans to renew the solution's latest version, but the hardware is around two years old.

Stability-wise, I rate the solution a nine out of ten. In the two years we have been using the platform, we have had only one or two issues that got the service out for a few hours.

The product's scalability is great. Scalability-wise, I rate the solution a ten out of ten.

I rate the technical support a nine to ten out of ten.

Positive

The initial setup was straightforward. Before IntelliFlex, we were using Teradata's 2700 and 2800 appliances. We were moving from a Teradata appliance to a new Teradata appliance, and during that process, we were able to move all the data in between three to six months without a problem, keeping both platforms working until we moved into IntelliFlex. The setup phase was a good process.

The solution is deployed on-premises. We are planning to move to the cloud in the future.

We feel that we are given the services from Teradata IntelliFlex for what we are paying. We are the Central Bank of Colombia, a non-profit organization, making it difficult for us to say that because of IntelliFlex, our earnings have increased. My institution doesn't aim for any earnings. We have been able to provide much better services to all of our customers, including all the financial institutions in our country, because of which I can say there has been a return on investment using Teradata IntelliFlex. A return on investment is possible based on the improvements in our service to our customers.

Our company is just looking to see if there is another product other than Teradata IntelliFlex that we can use in the future, not because we are not happy with the product. The reviews on Teradata IntelliFlex point out that it is a very solid and efficient solution, but we are slightly worried about the cost.

The price and the pricing structure should be improved.

Two years ago, we had plans to move into the cloud since we were doing so with all the products we have in our company to avoid having our own data centers. When we tried to move Teradata IntelliFlex to the cloud this year, we noticed that at this point in time, we might have to stay on-premises for a couple of years or until Teradata provides us with a better price structure. Owing to the aforementioned reasons, we have been considering moving to another more flexible platform and more price convenient for our company.

We are happy with the services provided by Teradata IntelliFlex.

At this point, it's worth looking at other alternatives other than Teradata IntelliFlex, depending on the kind of use you plan to do with the platform. There are certain areas of our company where we have noticed that we could get the same benefits from another platform, especially from the ones which are not pricey. If you really want to take advantage of the wonderful performance and speed that Teradata provides, then you need to choose it. But if you don't need the level of performance offered by Teradata, you can look for other alternatives. 

Overall, I rate the tool a nine out of ten.

We use Teradata to build data warehouses for our customers.

The ability to handle machine data parallel processing is the most valuable feature of Teradata. The fundamental design concept involves moving from Oracle's design process to achieving the best possible design. This represents a departure from traditional approaches and is an innovative idea introduced by Teradata in the industry. Many newer databases, such as Snowflake and Vertica, have adopted similar architectures.

Teradata can improve the way it handles big data and unstructured data.

I have been using Teradata for 16 years.

I give the stability of Teradata a ten out of ten.

I give the scalability of Teradata an eight out of ten.

The technical support is good and responsive.

Positive

The initial setup is straightforward. The deployment time is contingent upon the scale of the migration and moving from a lower to a higher environment is not a challenging task. The time it takes to migrate the data is also dependent on the source database and what ETL tool we are using. Around two to three engineers and one architect are required for the deployment.

We implement the solution for our clients.

Snowflake is built on top of the Teradata architecture but it has more flexibility.

I give Teradata an eight out of ten.

For enterprise-level organizations, Teradata is a suitable option.

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.

Aster Teradata is mostly being used for doing mapping and I use it for analytics. Usually, there is a support vendor who will use Teradata to do the database analytics. But sometimes with Teradata, the DB administrators use it to get access to the libraries or the data processes.  

I mostly recommend Teradata for data storage because it is easy to deploy and implement.  

The most useful features are the base product functionality of data storage and analytics. The ease of deployment is also useful so clients are implemented quickly.   

I think that a couple of things can be improved with this product. One is, of course, that there should be an option for using it on the Cloud. A lot of customers ask me how they can get up and running fast, and this would be the fastest way with the least client effort. I know Teradata already has its own Cloud solution, but I think that is one area that needs more maturation and exploration. We need to do more testing before we begin to recommend it to clients and we can do this because we work directly with Teradata. We are using the Cloud solution and it is more scalable and also the costs are fairly elastic. It should be something we are using more with clients in the future.  

At an organization level, I think sometimes the support for development is not forthcoming. It should become more of a part of their ongoing process. If they dedicate more resources to developing along with the latest trends in the industry, Teradata could then bring that functionality out for the current customers and maybe attract other customers as well.  

I would say that the company should consider more capabilities in handling unstructured data in a better way. Right now most of the latest solutions that are coming to the market address the need for how to take unstructured data and create a standard map for that. I think that would really help. Right now, I only see most of the data through Teradata with its unstructured processing and some of it is not available. They can do more with this. I think Teradata's mappings are good and very easy to use. I would use it for customer databases as it is. But there still some ways that the handling of unstructured data could be improved and that would really help.  

I've been doing technical solutions for data integration for 22 years. We have a relationship with Teradata for 11 years — since 2008. We implement solutions and have a lot of experience with this product.  

My team has had the opportunity to work with technical support. I think it is fair to rate their services as a three-out-of-five. I think they are somewhat above average.  

I think the team has been very happy with the setup of Teradata from the system side.  

It is taking about a week for deployment. To sort out the clients' needs on the level of technical reports and the results usually takes about two weeks. That is in addition to creating the data warehouse and loading the data.  

The feedback I get from customers is the cost is high for what they get. In many cases, another product — other than Teradata — could be better for our clients cost-wise. This is why we are continuing to explore options to see if there are other, more cost-effective solutions. That is an area of the product from Teradata that they need to evaluate.  

Teradata has all the best features currently, but I think right now the market is really flooding with multiple options. Many customers have a need for rapid on-premise deployment. I think in that case I would recommend Teradata. But for smaller or medium-sized companies, there are probably other options out there that they might use instead which will fit better for their budget.  

On a scale from one to ten where one is the worst and ten is the best, I would rate Aster Data MapReduce (Teradata) overall as maybe six or seven probably. Seven-out-of-ten.  

To improve that rating, I think we see that our customers have a lot of unstructured data. So in addressing that in a better way, Teradata would become an eight. It could possibly resolve this in a simple way with better integration in working directly with other solutions that are already available out there. This may be the best solution for that.  

We use it as a staging database in our organization, serving as a repository for financial models.

The current operational approach needs improvement. In the past, relying on infrastructure data staging provided flexibility in collaborating with any database provider. However, transitioning to Informatica and integrating it with various data services proved beneficial for serving multiple clients. Despite its advantages, this approach incurred substantial costs in terms of hardware and technical expertise. To address this, there is a need to develop and offer free content and workshops, providing guidelines and technical knowledge for efficient data operation.

I have been working with it for seven years.

I would rate its stability capabilities eight out of ten.

I would rate its scalability abilities six out of ten. While it provides scalability, it is notably complicated.

We previously used IBM, but due to the market requirements, we switched to Teradata.

The initial setup was straightforward.

It takes a couple of hours to be completely deployed.

It comes at a notably high cost for what it offers. Apart from the standard licensing fees, there are supplementary costs associated with the licensing course. I would rate it one out of ten.

Overall, I would rate it eight out of ten.

We use Teradata IntelliFlex for data warehousing, which is a way of presenting data for faster retrieval.

The solution's banking model, called FSLDM (Financial Services Logical Data Model), is sophisticated and good.

The solution’s pricing, scalability, and technical support response time could be improved.

I have been using Teradata IntelliFlex for one year.

Teradata IntelliFlex is a stable solution.

Since the solution is limited to its hardware, it has issues and limitations about scalability. Around 100 users are extensively using the solution in our organization.

The solution's technical support team is supportive but takes two to three days to respond.

Teradata IntelliFlex comes with hardware that is already deployed and preconfigured.

You purchase, deliver, and install the hardware and software to deploy the solution. People from Teradata will configure the software for you, and it will be ready.

Teradata IntelliFlex provides a lot of value to our organization.

Users have to pay a yearly licensing fee for Teradata IntelliFlex, which is very expensive.

Before choosing Teradata IntelliFlex, we evaluated other options like SQL Server and Oracle. We chose Teradata IntelliFlex because of its core competitive advantage in terms of a readymade model for the financial sector.

All analytics and reporting in our organization are done through the solution. Two people are required to maintain and operate the solution. We need five data modelers to design and develop the solution.

I advise users not to get stuck with the solution since it's expensive. The change on this platform is also expensive since it has so many associations with other layers. Currently, the new architecture for the data is to eliminate its complexity because it's a complex solution.

Overall, I rate Teradata IntelliFlex a seven out of ten.