We performed a comparison between BigQuery and Teradata Cloud Data Warehouse 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."The query tool is scalable and allows for petabytes of data."
"Even non-coders can review the data in BigQuery."
"It stands out in efficiently handling internal actions without the need for manual intervention in tasks like building cubes and defining final dimensions."
"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."
"There are some performance features like partitioning, which you can do based on an integer, and it improves the performance a lot."
"The initial setup is straightforward."
"The product’s most valuable feature is its ability to manage the database on the cloud."
"The setup is simple."
"The cloud is ten times better than physical hardware; it is more cost-effective and the upgrade process is ten times easier."
"The most valuable feature is the ease of running queries."
"The product is reliable."
"I rate BigQuery six out of 10 for affordability. It could be cheaper."
"With other columnar databases like Snowflake, you can actually increase your VM size or increase your machine size, and you can buy more memory and it will start working faster, but that's not available in BigQuery. You have to actually open a ticket and then follow it up with Google support."
"The initial setup could be improved making it easier to deploy."
"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."
"For greater flexibility and ease of use, it would be beneficial if BigQuery offered more third-party add-ons and connectors, particularly for databases that don't have built-in integration options."
"Some of the queries are complex and difficult to understand."
"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."
"They could enhance the platform's user accessibility."
"The cost of Teradata Cloud Data Warehouse has room for improvement."
"It could be a bit more user-friendly."
"Stability-wise, we have had some issues with automation and the ability to handle large datasets."
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BigQuery is ranked 5th in Cloud Data Warehouse with 31 reviews while Teradata Cloud Data Warehouse is ranked 13th in Cloud Data Warehouse with 3 reviews. BigQuery is rated 8.2, while Teradata Cloud Data Warehouse is rated 8.0. 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 Cloud Data Warehouse writes "Is quick, easy to upgrade, and cost-effective". BigQuery is most compared with Snowflake, Teradata, Oracle Autonomous Data Warehouse, Vertica and Apache Hadoop, whereas Teradata Cloud Data Warehouse is most compared with Snowflake, Amazon Redshift, Teradata, Oracle Exadata and Microsoft Azure Synapse Analytics. See our BigQuery vs. Teradata Cloud Data Warehouse report.
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