We performed a comparison between BigQuery and Teradata based on real PeerSpot user reviews.
Find out in this report how the two Cloud Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."I like that we can synch and run a large query. I also like that we can work with a large amount of data. You don't need to work separately, as it's a ready-made solution. It also comes with a built-in machine-learning feature. Once we start inputting the data, it will suggest some things related to the data, and we can come up with nice dashboards and statistics from a vast amount of data."
"It's straightforward to set up."
"The initial setup process is easy."
"It has a proprietary way of storing and accessing data in its own data store and is 100% managed without you needing to install anything. There is no need to arrange for any infrastructure to be able to use this solution."
"The product’s most valuable feature is its ability to manage the database on the cloud."
"The most valuable features of this solution, in my opinion, are speed and performance, as well as cost-effectiveness."
"One of the most significant advantages lies in the decoupling of storage and compute which allows to independently scale storage and compute resources, with the added benefit of extremely cost-effective storage akin to object storage solutions."
"The interface is what I find particularly valuable."
"Teradata can be easily used in ETL mode transformations, so there is no need for expensive and inconvenient ETL tools"
"We really enjoy the FastLoad, TPump, and MultiLoad features."
"It handles large amounts of information with a linear performance increase, in relation to a HW investment."
"The two types of partitioning have been very significant for us - row and columnar partitioning."
"It has given our business the ability to gain insights into the data and create data labs for analysis and PoCs."
"It is a stable program."
"I like this solution's ease of design and the fact that its performance is quite good. It is stable as well."
"Building a data warehouse with Teradata has definitely helped a lot of our downstream applications to more easily access information."
"The processing capability can be an area of improvement."
"It would be better if BigQuery didn't have huge restrictions. For example, when we migrate from on-premises to on-premise, the data which handles all ebook characters can be handled on-premise. But in BigQuery, we have huge restrictions. If we have some symbols, like a hash or other special characters, it won't accept them. Not in all cases, but it won't accept a few special characters, and when we migrate, we get errors. We need to use Regexp or something similar to replace that with another character. This isn't expected from a high-range technology like BigQuery. It has to adapt all products. For instance, if we have a TV Showroom, the TV symbol will be there in the shop name. Teradata and Apache Spark accept this, but BigQuery won't. This is the primary concern that we had. In the next release, it would be better if the query on the external table also had cache. Right now, we are using a GCS bucket, and in the native table, we have cache. For example, if we query the same table, it won't cost because it will try to fetch the records from the cached result. But when we run queries on the external table a number of times, it won't be cached. That's a major drawback of BigQuery. Only the native table has the cache option, and the external table doesn't. If there is an option to have an external table for cache purposes, it'll be a significant advantage for our organization."
"So our challenge in Yemen is convincing many people to go to cloud services."
"There are many tools that you have to use with BigQuery that are different services also provided for by Google. They need to all be integrated into BigQuery to make the solution easier to use."
"When it comes to queries or the code being executed in the data warehouse, the management of this code, like integration with the GitHub repository or the GitLab repository, is kind of complicated, and it's not so direct."
"An area for improvement in BigQuery is its UI because it's not working very well. Pricing for the solution is also very high."
"We would like to be able to calibrate the solution to run on top of a raw file."
"The solution should reduce its pricing."
"An additional feature I would you like to see included in the next release, is that it needs to be more cloud-friendly."
"The SQL Assistant is very basic. This tool can be improved for usability."
"There is some improvement required on OLTP level and some analytical function is missing."
"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."
"The solution needs improvement in its stability, support and pricing."
"The user interface needs to be improved."
"It could use some more advanced analytics relating to structured and semi-structured data."
"Teradata is an expensive tool. Like, if you're already using Microsoft products like Windows, they'll market all their products together. And with the rise of cloud technologies, companies will adopt solutions that offer them some privileges or facilities. Similar to how SAP does it in the market, so do Microsoft and other companies. Even Oracle and other such tools are quite commonly seen compared to Teradata's competitors in everyday solutions."
BigQuery is ranked 5th in Cloud Data Warehouse with 31 reviews while Teradata is ranked 3rd in Data Warehouse with 54 reviews. BigQuery is rated 8.2, while Teradata is rated 8.2. The top reviewer of BigQuery writes "Expandable and easy to set up but needs more local data residency". On the other hand, the top reviewer of Teradata writes "Offers seamless integration capabilities and performance optimization features, including extensive indexing and advanced tuning capabilities". BigQuery is most compared with Snowflake, Oracle Autonomous Data Warehouse, Vertica, Apache Hadoop and AWS Lake Formation, whereas Teradata is most compared with SQL Server, Snowflake, Oracle Exadata, MySQL and IBM Db2 Database. See our BigQuery vs. Teradata report.
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