Teradata Autonomous Knowledge Platform Reviews & Product Details

Speed on large datasets is the main reason we use it. We run analytical queries over tens of millions of rows daily. Before Teradata, those queries would time out or take twenty minutes. Now most finish in a few seconds.

The parallel processing handles volume differently than regular databases. Adding more nodes actually scales performance, so growth doesn't mean slowdowns. We've doubled our data volume in two years and query times stayed the same.

Being able to run Python analytics where the data lives saves us a ton of time. Our data science team used to extract data, move it to separate tools, run models, then bring results back. Now they write scripts that execute inside Teradata. No moving data around, no sampling, no waiting. Review collected by and hosted on G2.com.

The learning curve is steep. The platform has so many features that new team members spend weeks getting comfortable. It's not something you hand to a junior analyst on their first week. One new hire told me it felt like learning a new language.

Pricing is high compared to cloud alternatives. We looked at Snowflake and BigQuery recently. Both were cheaper for our usage patterns. But migrating off Teradata would be a massive project, so we're staying for now.

Documentation could be clearer. When we run into issues, finding answers sometimes means digging through support case comments instead of published docs. The community forums aren't as active as I'd like.

Query tuning for complex SQL is non-trivial. The explain plans aren't always easy to interpret, and optimization often requires deep expertise. Our best analyst spends a lot of time on this. Review collected by and hosted on G2.com.

I like Teradata Vantage for its performance and scale. Its massively parallel processing architecture distributes queries across thousands of nodes simultaneously, making it perfect for petabyte-scale data without performance degradation. The major optimizer is perfect, and I appreciate the workload management and qualified calls. Hybrid cloud flexibility and high concurrence are also standout features, along with its rock-solid reliability and built-in data protection. Review collected by and hosted on G2.com.

The cost is really the biggest barrier by far. Licensing is enterprise-level expensive, and the pricing model isn't transparent. The UI/UX also could be improved. The setup and administration, the cloud-native field, and the developer experience as well could be better. The initial setup was really not that easy and it requires specialized DBAs for on-prem deployment. Vantage on cloud is easier, but it's not that simple. Review collected by and hosted on G2.com.

I use Teradata Vantage for various tasks like figuring out customer churn rate and running Python scripts against my large datasets. The biggest headache it saves me from is the long waiting time for getting the required data. I no longer need to export data to CSV; I can directly query Teradata Vantage and get results promptly. I like the SQL engine's power of Teradata Vantage the most because joining queries on millions of rows just works like a charm. Instead of searching through the whole table, it goes straight to the record. Teradata Vantage's primary index strategy is what makes it faster than other tools out there. Setting it up with Azure was easy, especially after following the documentation correctly. Review collected by and hosted on G2.com.

Honestly for the scale i'm working at, i havent found any shortcomings yet in Teradata Vantage Review collected by and hosted on G2.com.

I like that Teradata Vantage solves the concurrent problem well. We have a lot of people using it simultaneously, with analysts running ad-hoc queries, dashboards refreshing, and ETL jobs running in the background. The workload management handles all of that without things falling over. It also provides one place where all our data lives, which has helped a lot with everyone having a 'single source of truth.' Review collected by and hosted on G2.com.

Learning curve is rough. Like, if you are new to Teradata you are gonna write queries that run forever and you won't know why, and then someone senior is gonna look at it and go 'your primary index is wrong' or 'you've got skew'. Also, the tools feel old. Review collected by and hosted on G2.com.

I use Teradata Vantage for data warehousing and running complex SQL queries. I appreciate its strong performance with datasets and its ability to manage and analyze large data efficiently. The stability and parallel capabilities are quite impressive, helping me process large amounts of data quickly without performance issues. After migrating from an on-premise data warehouse solution, I've noticed improved stability and performance, which has been really beneficial. The transition was smooth, and my team, who initially found it very easy to set up, is now enjoying using it. Review collected by and hosted on G2.com.

Maybe you could make it easier for new joiners. The setup and administrative process can seem a bit complicated at the beginning. Review collected by and hosted on G2.com.

So i did some poc using agent builder it built some poc around parallelization design of agent flow which really helpful and used its vector store for the rag pipeline i Integrated 1 agent with the rag pipeline tge integration within the tools are seemless. Review collected by and hosted on G2.com.

Budget might overkill for small projects, l feel the ui needs to be veey engaging and responsive when we use a no code, low code tool i feel it to be bit non responsive as expected sometimes while making the workflows. Review collected by and hosted on G2.com.

I like Teradata Vantage's scalability and speed in processing large datasets, which makes analytics much more efficient. Its scalability lets us expand analytics as data grows without performance loss, while the speed shortens query times, helping teams access insights faster and make timely decisions. Review collected by and hosted on G2.com.

Some features feel complex to configure, and the interface could be more intuitive for new users. Advanced configuration options can be complex, especially around workload management and query optimization. The interface could be more user-friendly with cleaner navigation and simplified dashboards for new users. It required some technical expertise, especially around configuration. Review collected by and hosted on G2.com.

I like Teradata Vantage's ability to handle very large datasets efficiently without major performance issues. It processes complex queries quickly, making reporting and analysis much more reliable and efficient. We also use it with reporting tools like Power BI and integrate it with our cloud storage, which has been quite useful. Review collected by and hosted on G2.com.

I believe one area could be the overall UX and ease of use as it can be difficult for new users. Specific aspects would be query optimization, navigation and understanding how different tools work together. The UX is not as intuitive. Review collected by and hosted on G2.com.

The advantage we get is that we have multiple systems or DB's which are legacy and some are new. Vantage helps us unify all their data stream into one Review collected by and hosted on G2.com.

Some legacy softwares are incomaptible with Vantage. This causes some issues with us either mnaually adding this data in our pipeline or using a mapper function Review collected by and hosted on G2.com.

It supports various analytic types (SQL, ML, AI , geospatial) on a single platform. And it has deployment flexibility. One other thing I like is that it is secure. Review collected by and hosted on G2.com.

It is expensive as compared to other competitors. It is a bit complex and challenging for new users, not much user friendly. The user interface is very outdated. Review collected by and hosted on G2.com.