We performed a comparison between BigQuery and Oracle Autonomous 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 setup is simple."
"The product’s most valuable feature is its ability to manage the database on the cloud."
"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."
"It's straightforward to set up."
"We basically used it to store server data and generate reports for enterprise architects. It was a valuable tool for our enterprise design architect."
"The most valuable features of BigQuery is that it supports standard SQL and provides good performance."
"BigQuery excels at structuring data, performing predictions, and conducting insightful analyses and it leverages machine learning and artificial intelligence capabilities, powered by Google's Duarte AI."
"There are some performance features like partitioning, which you can do based on an integer, and it improves the performance a lot."
"It provides Transparent Data Encryption (TDE) capabilities by default to address data security issues."
"With Oracle Autonomous Data Warehouse, things are much simpler. Creating a structure, initializing the servers, extending the servers, those are all things that are very, very easy. That's the main reason we use it."
"It is an extremely scalable solution since you can dynamically change the resources as some other cloud solutions."
"One advantage is that if you already have an Oracle Database, it easily integrates with that."
"The solution integrates well with Power BI."
"The analytics have been very good. We've found them to be quite useful."
"Oracle Autonomous Data Warehouse is used globally to deliver extreme performance on large Financial data sets."
"Self-patching and runs machine-learning across its logs all the time"
"The primary hurdle in this migration lies in the initial phase of moving substantial volumes of data to cloud-based platforms."
"The main challenges are in the areas of performance and cost optimizations."
"The solution hinges on Google patterns so continued improvement is important."
"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."
"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."
"There is a good amount of documentation out there, but they're consistently making changes to the platform, and, like, their literature hasn't been updated on some plans."
"There are some limitations in the query latency compared to what it was three years ago."
"The processing capability can be an area of improvement."
"I would like to see an on-premise solution in the future."
"A lot of the tools that were previously there have now been taken away."
"It is very important the integration with other platforms be made to be as easy as it is with an on-premises deployment."
"One of the major problem is creating custom tablespace. The ADB serverless option doesn't support custom tablespace creation, which could cause issues during on-premise database migration that requires specifically named tablespace. There should be an option to create customized tablespace."
"Sometimes the solution works differently between the cloud and on-premises. It needs to be more consistent and predictable."
"They should make the solution more user-friendly."
"I would like to see Application Express and Oracle R Enterprise fully supported, and I would like to see Oracle Data Mining supported as a front end."
"The solution lacks visibility options."
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BigQuery is ranked 5th in Cloud Data Warehouse with 31 reviews while Oracle Autonomous Data Warehouse is ranked 10th in Cloud Data Warehouse with 16 reviews. BigQuery is rated 8.2, while Oracle Autonomous Data Warehouse is rated 8.6. 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 Oracle Autonomous Data Warehouse writes "A tool for data warehousing that offers scalability, stability, and ease of setup". BigQuery is most compared with Snowflake, Teradata, Vertica, Apache Hadoop and AWS Lake Formation, whereas Oracle Autonomous Data Warehouse is most compared with Oracle Exadata, Snowflake, Microsoft Azure Synapse Analytics, Amazon Redshift and Teradata. See our BigQuery vs. Oracle Autonomous Data Warehouse report.
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