We performed a comparison between BigQuery and Teradata Cloud Data Warehouse based on real PeerSpot user reviews.
Find out what your peers are saying about Snowflake Computing, Microsoft, Amazon Web Services (AWS) and others in Cloud Data Warehouse."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 most valuable features of this solution, in my opinion, are speed and performance, as well as cost-effectiveness."
"The solution's reporting, dashboard, and out-of-the-box capabilities match exactly our requirements."
"The integrated data storage features are good."
"The initial setup is straightforward."
"The product is serverless. We only need to write SQL queries to analyze the data. We need to pay based on the number of queries. The retrieval time is very less. Even if you write large queries, the tool is able to bring back data in a few seconds."
"The initial setup process is easy."
"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."
"The most valuable feature is the ease of running queries."
"The cloud is ten times better than physical hardware; it is more cost-effective and the upgrade process is ten times easier."
"The product is reliable."
"There are some limitations in the query latency compared to what it was three years ago."
"The price could be better. Compared to competing solutions, BigQuery is expensive. It's only suitable for enterprise customers, not small and medium-sized businesses, as they cannot afford this kind of solution. In the next release, it would be better if they improved their AI bot. Although machine learning and artificial intelligence are doing wonders, there is still a lot of room to enhance them."
"I would like to see version-based implementation and a fallback arrangement for data stored in BigQuery storage. These are some features I'm interested in."
"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."
"The product’s performance could be much faster."
"It would be beneficial to integrate additional tools, particularly from a business intelligence perspective."
"I noticed recently it's more expensive now."
"The main challenges are in the areas of performance and cost optimizations."
"It could be a bit more user-friendly."
"The cost of Teradata Cloud Data Warehouse has room for improvement."
"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.
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