Teradata VantageCloud Enterprise (SaaS) *Australia*

Teradata  is primarily used for data warehousing across all customers. My clients have built-in applications that use Teradata , and their use varies from customer to customer, depending on the industry and database size. The primary function is as an OLAP analytical ecosystem.

Scalability is excellent because of Teradata's parallelism. It doesn't impact operations when nodes are added. This allows customers to expand without migrating the entire database or system.

The most valuable aspects of Teradata are not specific features. Rather, it's the overall performance, particularly parallelism, workload management, and parallel computing. Teradata effectively uses parallelism to the granular level, performing better than other databases.

Teradata is somewhat late in adopting cloud technology. They need to focus on the adoption of cloud to remain competitive and target customers who prefer not to invest in capital expenditures and seek a more flexible, operational expenditure approach.

I have worked with Teradata for around 15 years, from Teradata version six to version 14.

Teradata is highly stable. The workload management and software maturity provide a reliable system, unlike some newer cloud software that can exhibit misbehavior.

Even if an organization starts small, Teradata offers the flexibility to expand by adding nodes or more storage, especially in cloud environments, without incurring downtime or taking systems offline.

The technical support from Teradata is quite advanced. However, like any support service, there can be delays. I rate the support as eight out of ten because of their technical expertise.

Positive

During my career, I've been involved primarily with Teradata, and some clients are migrating from Teradata to other technologies.

The initial setup process is rated as eight out of ten. It's straightforward. That said, when migrating databases from other systems, challenges arise in redesigning the code to optimize parallelism.

The implementation is managed by a separate customer service group within Teradata, not by me or my group.

Teradata is high-quality at a premium price. Initially, it may seem expensive compared to similar cloud databases, however, it offers significant value in performance, stability, and overall output once in use.

New users should focus on understanding Teradata's parallelism and write their queries or codes to utilize its full potential. Knowing how to use workload management effectively is beneficial.

I'd rate the solution eight out of ten.

Our primary use case for Teradata is as a data warehouse; we store our databases for the data warehouse, including the EDW. It is mainly used for our data warehouse environment where we run a lot of analytics and heavy queries.

The solution provides good performance for our analytics queries. Due to the capacity of the Teradata warehouse, our queries are well performed.

The data mover is valuable over the last two years as it allows us to achieve data replication to our disaster recovery systems. We use the Teradata mover utility, which is presently valuable.

Replication needs improvement because we currently use DataMover once daily. Unlike SQL and Oracle, which have in-built replication capabilities, we don't have similar functionality with Teradata. 

Additionally, when backups are performed, it locks the database, preventing user access, which is a concern. Also, we need extra servers to perform backups, unlike SQL, which has embedded backup capabilities.

I have been working with Teradata for the last four years.

I find the stability to be almost a ten out of ten. It is very stable in our experience.

Scalability is complex as you need to purchase a license and coordinate with Teradata for additional disk space and CPU. They enable a small percentage for scaling, which isn't straightforward.

Customer support is very good, rated eight out of ten under our essential agreement, although it depends on the license agreements.

Positive

We also use SQL and Oracle. Teradata is much more expensive, however, it was already in place at our company.

The setup process is complex. Teradata installed and configured the systems.

We used Teradata's services for installation and configuration.

The pricing is quite high. It's a two out of ten where one is very high priced. Teradata is much more expensive than SQL, which is well-performed and cheaper.

I prefer SQL for its cost-effectiveness and performance and also consider Oracle, although its licensing is more expensive. Teradata was already present when I joined the company.

For Teradata to perform well, it requires good configuration and a good structure of the database. It's most suitable for medium and above-sized companies rather than small ones.

I'd rate the solution seven out of ten.

It’s good. The educational resources are good. I think the idea of distributed computing is well implemented in Teradata, and that was likely their intention from the beginning. It's a foundation for big data processing. So far, I appreciate the product, but I haven't worked on a real project with it yet.

The courses are good. I don’t have a full certification yet; I just have some course certificates. In my first week, I completed around five or six courses, and now I work on a longer one. The content is well-organized, and I’m happy with the learning materials so far.

The data processing, clustering, and distributed computing are impressive. I’m curious to see how it works internally and how performance is accelerated. I’m also learning about how SQL and Teradata’s EXPLAIN feature work. So far, it's a very good product.

Teradata do have some AI models that can be used for in-database analytics. I haven’t tried them yet, but I know the product's K-Means implemented in the database, which is interesting because I’ve seen how challenging it is to parallelize K-Means in other environments. I plan to explore it more when the opportunity arises.

K-Means is implemented, and Teradata leverages its database operations for AI analytics. They use parallel processing, which is one of Teradata's main features.

I find Teradata's approach useful in its current state. I definitely want to explore it further.

Teradata has a few AI models, but in data science, we need more flexibility. We can’t be limited to what's pre-built in the database. Typically, data science projects require experimenting with different models, so the limitation is that Teradata only has basic machine learning models in its database. Data science requires more advanced modeling, and you always want to search for the best possible approach. Combining the capabilities of Teradata with custom data science models will take time to mature, but it shows promise.

Teradata needs to promote it more. If they're the first to introduce things like in-database AI, they should really focus on promoting that. I haven't heard much about it, but maybe that's because the environment I’ve been working in recently has been mostly open-source. I’ve been doing applied research and freelance work that didn’t rely on robust vendor products, so I never got a chance to compare Teradata to others. I have heard about Databricks, though.

I started using it this month, so my experience is very recent.

I've worked a lot with open-source tools, mainly Python, in my role.

I’ve worked with IBM Cognos before, but that was just part of a solution, mainly for VPN dashboards. However, I wasn’t a specialist in business intelligence, so this is new to me. Teradata complements my data science journey.

From my perspective, I only started using it because it's needed for my current job. Before this, I didn't consider Teradata better than Oracle or GV2A. I think it's better than GV2A, but Oracle is more robust. Teradata has its customers, but I didn’t really compare them before because business intelligence and data warehousing were not my areas of focus. IBM was behind both Oracle and Teradata in this field, but I am not sure exactly how Teradata stands in comparison. 

In my data science journey, I realized that my weak point was data analysis and data warehousing, which is why I’m happy to be working with Teradata now. It's helping me fill that gap.

I’ll be recommending it to customers. In my country, it is very active in acquiring data analysis solutions, so it will likely be recommended for that sector.

I have very limited knowledge at this point. I'm still exploring the architecture. From what I’ve learned so far, I believe it's used quite extensively in my region. The idea of distributed computing and partitioning is definitely something that's needed.

Also, the cloud and on-premises architectures are not that different, which is a positive aspect.

Overall, I would rate the product 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. 

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.