We performed a comparison between Oracle Autonomous Data Warehouse and Snowflake 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 loved the simplicity of loading the data and simply relying on the self-tuning capabilities of ADW."
"The solution is self-securing. All data is encrypted and security updates and patches are applied automatically both periodically and off-cycle."
"One advantage is that if you already have an Oracle Database, it easily integrates with that."
"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."
"The solution integrates well with Power BI."
"I really like the auto-tuning, auto-scaling, and the automatic load balancing and query tuning in the system."
"Oracle Autonomous Data Warehouse is used globally to deliver extreme performance on large Financial data sets."
"The performance and scalability are awesome."
"The solution is very easy to use."
"Its speed and performance were the most valuable. Easy configuration of Snowflake in any cloud was also a benefit."
"The most valuable features are sharing data, Time Travel, Zero Copy Cloning, performance, and speed."
"The speed of data loading and being able to quickly create the environment are most valuable."
"Its performance is a big advantage. When you run a query, its performance is very good. The inbound and outbound share features are also very useful for sharing a particular database. By using these features, you can allow others to access the Snowflake database and query it, which is another advantage of this solution. It has good security, and we can easily integrate it. We can connect it with multiple source systems."
"Can be leveraged with respect to better performance, auto tuning and competition."
"This solution has helped our organization by being easy to maintain and having good technical support."
"The solution speeds up the process of onboarding."
"The installation process is complex. Oracle can make the installation process better."
"There is a need for more storage to be allocated, but over a period of time, it becomes impossible to reduce it after using it."
"An improvement for us would be the inclusion of support for an internal IP, so we could use it directly with the VCN in Oracle Cloud."
"The initial setup was pretty complex. It was not easy."
"A lot of the tools that were previously there have now been taken away."
"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."
"I would like to see an on-premise solution in the future."
"It doesn't work well when you have unstructured data or you need online analytics. It is not as nice as Hadoop in these aspects."
"The solution should offer an on-premises version also. We have some requirements where we would prefer to use it as a template."
"There is room for improvement in Snowflake's integration with Python. We do a lot of SQL programming in Snowflake, but we go to a different tool to program when we have to in Python."
"They have a new console, but I couldn't figure out anything in the new console. So, if I shift to the old console, I can figure out where to create the database schema and other things, but I have no idea where to go in the new console. That's one thing they can improve. I don't know why they created a new console to confuse. The old, classic console is much better."
"Snowflake needs to improve its programming part. Though the tool has Snowpath, it doesn’t support all features like its competitor, Databricks. Snowflake doesn’t support external data ingestion capabilities. You need to have third-party tools for that. Also, the tool needs to incorporate data integration features in its future releases."
"We would like to be able to do modeling with Snowflake. It should support statistical modeling."
"Product activation queries can't be changed while executing."
"Snowflake could improve if they had an Operational Data Store(ODS) space."
"They need to incorporate some basic OLAP capabilities in the backend or at the database level. Currently, it is purely a database. They call it purely a data warehouse for the cloud. Currently, just like any database, we have to calculate all the KPIs in the front-end tools. The same KPIs again need to be calculated in Snowflake. It would be very helpful if they can include some OLAP features. This will bring efficiency because we will be able to create the KPIs within Snowflake itself and then publish them to multiple front-end tools. We won't have to recreate the same in each project. There should be the ability to automate raised queries, which is currently not possible. There should also be something for Exception Aggregation and things like that."
More Oracle Autonomous Data Warehouse Pricing and Cost Advice →
Oracle Autonomous Data Warehouse is ranked 10th in Cloud Data Warehouse with 16 reviews while Snowflake is ranked 1st in Cloud Data Warehouse with 94 reviews. Oracle Autonomous Data Warehouse is rated 8.6, while Snowflake is rated 8.4. The top reviewer of Oracle Autonomous Data Warehouse writes "A tool for data warehousing that offers scalability, stability, and ease of setup". On the other hand, the top reviewer of Snowflake writes "Good usability, good data sharing and elastic compute features, and requires less DBA involvement". Oracle Autonomous Data Warehouse is most compared with Oracle Exadata, Microsoft Azure Synapse Analytics, BigQuery, Amazon Redshift and Teradata, whereas Snowflake is most compared with BigQuery, Azure Data Factory, Teradata, Vertica and SAP BW4HANA. See our Oracle Autonomous Data Warehouse vs. Snowflake report.
See our list of best Cloud Data Warehouse vendors.
We monitor all Cloud Data Warehouse reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.