We performed a comparison between BigQuery and Oracle Exadata 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."It's pretty stable. It's fast, and it is able to go through large quantities of data pretty quickly."
"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 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."
"The feature called calibrating the capacity is valuable."
"As a cloud solution, it's easy to set up."
"It has a well-structured suite of complimentary tools for data integration and so forth."
"The solution's reporting, dashboard, and out-of-the-box capabilities match exactly our requirements."
"It is the best solution for OLTP and data warehousing."
"Oracle Exadata is stable."
"Backup/Restore performance: Fast backups, fast restores (especially useful for creating clone environments)."
"The performance on the databases is good."
"The most valuable feature of Oracle Exadata is its capabilities for storing and processing data. It is very good for our domain."
"Exadata is a fantastic machine. Two features stand out. The first is the resource input/output management tool that allows you to manage the resources to the neck on the Exadata box."
"The performance of the data is the most important part."
"Exadata's best features are its performance during redo logging and the elasticity of the database handling."
"The primary hurdle in this migration lies in the initial phase of moving substantial volumes of data to cloud-based platforms."
"The solution should reduce its pricing."
"The main challenges are in the areas of performance and cost optimizations."
"I rate BigQuery six out of 10 for affordability. It could be cheaper."
"The product’s performance could be much faster."
"There are some limitations in the query latency compared to what it was three years ago."
"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 solution hinges on Google patterns so continued improvement is important."
"We have a little trepidation with the system as it does have a learning curve. Also changing to a binary logging format for us feels like retrograde motion, but sadly almost all Linux variants have moved in this direction."
"We had issues with system restoration."
"The cost of the solution is high and can be improved."
"I have found Oracle Exadata to be scalable. However, you have to purchase more hardware, such as memory."
"We used the support from Oracle Exadata to complete the implementation."
"The solution lacks a visualized console."
"Oracle Exadata could improve the platform performance tuning should be easier, automated, and user-friendly."
"Oracle Exadata could improve the monitoring system in the enterprise manager, it could be more user-friendly. In most Oracle tools there is a lot of functionality, and sometimes you need to do five or six clicks to find metrics, and sometimes it's a waste of time."
BigQuery is ranked 5th in Cloud Data Warehouse with 31 reviews while Oracle Exadata is ranked 2nd in Data Warehouse with 124 reviews. BigQuery is rated 8.2, while Oracle Exadata is rated 8.4. 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 Exadata writes "Offers a variety of valuable features". BigQuery is most compared with Snowflake, Teradata, Oracle Autonomous Data Warehouse, Vertica and Dremio, whereas Oracle Exadata is most compared with Oracle Database Appliance, Teradata, Oracle Autonomous Data Warehouse, Snowflake and Teradata Cloud Data Warehouse. See our BigQuery vs. Oracle Exadata report.
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