Teradata Reviews

Our use cases are all about data ingestion, data manipulation, and data exploration. It's the core database for us.

It's the same as your visual database. I like the fast load feature for data, BTQ nd storage procedures are very good. They can avoid table locking, which is very good.

Sometimes the large ingestion jobs takes days to load data, and some of our stored procedures take longer. I don't know whether it's the tool or the network, but it takes a long time to execute complex commands.

I've been using this solution for around five years Now. We currently use the latest version. 

It is a stable solution. I would rate the stability a nine out of ten.

I would rate the scalability a nine out of ten. It is scalable. 

There are more than 100 users currently using Teradata in our organization.

The customer service and support are good. But they take a long time to respond.

So there is room for improvement in response time. 

It's a very straightforward installation process. It's good in terms of installation.

The solution requires maintenance. Our team of ten engineers manage and maintain the solution.

It is yearly basis. The licensing is based on a contract. It's a very expensive product.

I would rate the pricing model a three out of ten, where one is very expensive and not cost-effective, and then ten is a very cheap product. The solution is fairly expensive. 

Overall, if I consider the expense, features, and everything, then I would rate the solution a six out of ten.

We have all our workloads on AWS.

Having Teradata in AWS:

• Helps us with connectivity.
• Making sure the data is secure.
• Reduces the hops.
• Helps us more with real-time data.

We had few reports which were taking more than 45 minutes. Then, with Teradata, we received results within minutes, and a few under a minute. We thought that something went wrong, and we hadn't done the work properly, but we saw the exact same results on both. So, our end users were pretty happy.

It is quick, secure, and has less hassles because we don't have to involve our networking team, infrastructure, etc. It is very easy to deploy and make market ready.

Teradata wants to come out of the hardware business and to run its own cloud on other public clouds. I think that is a great way to go. However, there are challenges to doing this. There are multiple layers of security and caching. E.g., if you have a lot of compute or a caching that will offload a lot of compute activity because it's already there, it will save its cycles for something which needs to be done. This way, you are offloading your compute, so you can go with a lesser capacity than a higher capacity. That is what this appliance does.  If they are moving off of the appliance, I am curious to see if their software will withstand the change, or will Teradata still run but need a bigger box?

I would like more security and speed. These days, everyone is not just moving to cloud, but they are moving to clout. In a multi-cloud environment, you have to be cognizant of data transfer, bandwidth, and egress charges, not just from a performance and scalability point of view, but also how to keep costs low.

We haven't had any outages in one and a half years. That is a good statement.

I have not heard anyone complain about performance.

The technical support is pretty good. The response rate is good.

We had a bunch of legacy warehouses, which we wanted to consolidate, as well as stay up-to-date with warehousing options. This is why we moved into Teradata.

The integration and configuration were seamless for us.

We have multiple sources of data, so Teradata has a lot of connectors which pulls all our data from different workloads. The integration works really well.

We had help with the integration and configuration.

When your customer is happy, dollars and cents sort of blur. Our return on investment would be customer satisfaction, which I think is priceless.

We had a lot of parties involved when purchasing from the AWS Marketplace. They are very flexible and aggressive in trying to close the deal. They are good at what they have to offer and listening to the customer. It's a two-way street.

In this day and age, we want to get things done quickly. So, we go to the AWS Marketplace.
Also, we have a consistent experience with Teradata usage on its cloud, so we already know the product.

For what Teradata has to offer, their price is comparable to its competitors.

We evaluated Redis and Teredata, doing PoCs with both. We had more support from Teradata to start with, and we were new to both. We were not in a situation to tell which one was good, because both were new to us. We just had more support from Teradata to help us see the results on what we are looking for.

Do your homework before you make a decision. Everyone is different; every shop is different. That is what makes it fun to be in IT.

When you look for a solution, you will uncover many advantages. All those hidden things which are not clear initially when you do a cost analysis. A cost analysis is something that you have to do from the get-go, but it also has to be an ongoing process. Your workloads change, requirements change, everything changes, so it has to be a constant feedback.

We have used both the on-premise and AWS versions.

Teradata is a great, industry-leading data warehousing product that has MPP architecture. In recent times, there have been many other products available in the cloud space. It has a lot of other features like linear scalability and unconditional parallelism.

Teradata hardly supports unstructured data or semi-structured data. Teradata is very costly, and it's not easy to upgrade or expand the components in Teradata. A lot of infrastructure needs to be set up in order to use Teradata.

I have been using Teradata for more than 15 years.

Teradata is a very expensive solution.

Many other products equivalent to Teradata are available in the market, like BigQuery, Redshift, and Snowflake.

Teradata is a suitable solution for small customers.

Overall, I rate Teradata an eight out of ten.

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 it primarily as a dedicated platform for aggregating structured data, essentially serving as our structured data repository or data warehouse.

Their extensive experience in data warehousing, the platform's performance, and their strong reputation in the market are the most valuable.

One issue we've identified is that its performance varies across different on-premises setups and doesn't consistently meet our standards. This limitation necessitates the purchase of Teradata's proprietary hardware to ensure the desired level of performance. The capability to implement it with comparable performance across various private cloud environments, ensuring adaptability to different infrastructure setups would be beneficial.

I have been using it for four years.

The stability is excellent, and I would rate it nine out of ten.

The challenge lies in the necessity to purchase additional hardware for scaling, so I would lean towards a rating of around four out of ten for the overall experience.

The technical support is satisfactory; I would rate it seven out of ten.

Neutral

I would rate the initial setup six out of ten when it comes to complexity.

I would rate the return on investment eight out of ten.

The cost is significantly high. I would rate it eight out of ten.

Overall, I would rate it seven out of ten.

There are two very useful features. 

One is the fast data input for more or less any online data. It performs rather well. Two, it also has a lot of tools for data engineering or data manipulation that are compatible. 

The solution offers an easy setup.

It's stable and reliable.

The solution like scales just fine.

Some of our clients are looking for on-premise installations as well. Although we don't have any, some of our prospects are also asking, and we are not sure if that part is easily doable or is as effective. We haven't tried on-premises, so we don't know how good it is. We are not confident about proposing on-premise to them, since we are more familiar with the cloud. Maybe some documentation on how on-prem works or what other things to look for in on-premise deployment would be helpful. We'd love to see more tutorials. 

Our company does data science and AI machine learning algorithms on the data that is deciding on the Teradata, so that's the value we add. From my perspective, it would be good if they gave better ITIN/R plugins to use the data for AI modeling, or data science modeling. We can do it now; however, it could be more elegant in terms of interfacing.

I've been using the solution for four or five years. 

The solution is very stable, and the performance is good. It's reliable. There are no bugs or glitches. It doesn't crash or freeze. 

Our clients do not have very large data sets. So far, the environment has scaled fine, however, once the volumes grow, we will have to see whether we are facing any problems or not. Right now, we don't see any problems. We just haven't tried to scale massively.

We haven't needed much technical support. That said, some of my colleagues have been able to contact them and get service as and when required. It's all right. 

Positive

On cloud, it is very easy to set up. 

It's moderately priced. It's not cheap. I'd rate it 2.5 out of five in terms of affordability.

I am not knowledgeable about the other vendors to make a meaningful comparison. I haven't really taken the time to evaluate other options. 

The solution is most suitable for medium to large-scale businesses. 

I'd rate the solution seven out of ten.

I would recommend the solution to others. 

IntelliFlex is used in the banking sector as a production system.

IntelliFlex's best feature is its reliability.

I've been using IntelliFlex for three years.

IntelliFlex is very stable, aside from some issues with the Unity Software, though I believe those are being resolved now.

IntelliFlex is easy to scale - one of its best features is that you can upscale it to the size you want. For example, we started in vertical with a six-node system and now have a twenty-four-node system.

IntelliFlex's technical support is excellent.

Positive

The initial setup is complex because there are a lot of factors that come into play, including the amount of software and applications that require access. Deployment takes around two to four months, assuming that all the company's applications are compatible with the system - if not, it may take longer.

IntelliFlex is the Rolls Royce of data warehousing. I would recommend it to other users and rate it nine out of ten.

We currently use the on-prem model of this solution. Our primary use case of this solution is as an enterprise tech warehouse for business intelligence across different domains. 

We've been using Teradata for close to twenty years and this version is a lot faster and more improved than the previous version that we used. It gives us more. It gives us the ability to be more resilient. It has fallback on default. We always have a copy of the copied data. There's more resilience and from a banking perspective, that is a good thing. 

Having continual fallback is good for security. We use the standard TTU utilities. That's what we use with all the different versions. It's faster and more resilient. 

They should add more connectors to different platforms. 

It could use a more powerful CPU and a faster IO. 

It is very stable. It's 100% uptime. Speed and resilience are one of the greatest features of this product. In almost twenty years we've never had downtime, except for outages for patches and upgrades. We've never had a system failure in twenty years. 

Its scalability is first class. We can easily add more nodes to it. We have around three to four thousand users. 

We have 100 people maintaining different applications. We don't currently have major plans to increase usage.

Their technical support is excellent. If you have a P1 you call within the hour. 

The initial setup was straightforward. We didn't have any problems installing the new platform. The deployment took six months. 

We implemented it ourselves. 

We didn't evaluate other options because we've been using Teradata for 20 years. We update versions. 

It's an excellent product. It's tried and tested with large organizations. The on-prem product is very powerful. Teradata has a cloud option. Both are good options. It depends on what your organizational plans are. 

I would rate this solution a nine out of ten.