We performed a comparison between Microsoft Azure Synapse Analytics 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 initial setup is very simple."
"The most valuable features of Microsoft Azure Synapse Analytics are its serverless flexibility and complete power have allowed me to explore various different use cases. While I am not an expert in the product, my experience in programming in Databricks has shown me that Microsoft's investments in Synapse could potentially lead to it becoming a complete replacement for Databricks in the future."
"I like the keynotes and their simplicity. Like other Microsoft products, Microsoft Azure Synapse Analytics is simple to understand and use."
"The most valuable features are the flexibility and that it's easy to use as an end-user compared to AWS."
"The most valuable feature is performance gains."
"One of the most valuable features of this solution is its ability to integrate well with other services offered by Azure."
"Scaling this solution is easy and the uptime is okay."
"I think the most valuable component is that pipelines are built into it and then the feature that you can mirror a cosmos BB for analytics."
"The product is easy to use."
"The analytics have been very good. We've found them to be quite useful."
"The performance and scalability are awesome."
"The solution integrates well with Power BI."
"Oracle Autonomous Data Warehouse is used globally to deliver extreme performance on large Financial data sets."
"It is a very stable tool...It is an extremely scalable tool."
"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 major challenge that we're seeing with Azure Synapse is around security concerns. The way it is working right now, it has Managed VNet by Microsoft option, similar to the implementation of Azure Databricks, which may pose a concern for financial institutions. For managed environments, the banks have very strict policies around data being onboarded to those environments. For some confidential applications, the banks have the policy to encrypt it with their own key, so it is sort of like Bring Your Own Key, but it is not possible to manage the resources with Microsoft or Databricks, which is probably the major challenge with Azure Synapse. There should be more compatibility with SQL Server. It should be easier to migrate solutions between different environments because right now, it is not really competitive. It is not like you can go and install SQL Database in some other environment. You will have to go through some migration projects, which probably is one of the major showstoppers for any bank. When they consider Synapse, they not only consider the investment in the actual service; they also consider the cost of the migration process. When you scale out or scale down your system, it becomes unavailable for a few minutes. Because it is a data warehouse environment, it is not such a huge deal, but it would be great if they can improve it so that the platform is available during the change of configuration."
"We'd, of course, always like to pay less for the service if we can."
"An area for improvement in Microsoft Azure Synapse Analytics is its user interface. You can use it for analytical purposes, but its platform should be a little bit more user-friendly. Another small point for improvement in Microsoft Azure Synapse Analytics is its stability. It's good currently, but it could still be improved. Microsoft is combining different tools and technologies into one solution, so in the future, I'm expecting to see even more improvement in Microsoft Azure Synapse Analytics. An additional feature I'd like to see in the next version of Microsoft Azure Synapse Analytics is the drag-and-drop feature. If you're doing some integrations where you can write Scala or you have SPARK programming or SQL, or you're combining different programming, the process should be seamless, and you should be able to drag and drop in Microsoft Azure Synapse Analytics. When doing reporting in the solution, you should also be able to drag and drop. There should be connectors available and a drag-and-drop feature available in the user interface of Microsoft Azure Synapse Analytics, so you won't have to worry about how all processes would work together. You need to be able to drag and drop even from the backend, and having this feature will make the solution more user-friendly."
"One area for improvement could be better integration with Power BI, as well as data integration with BW."
"It could be beneficial to focus on integration with various data sources and similar enhancements."
"I'd like to see part of the service de-coupled."
"The only concern for us is the cost part. When it comes to the implementation and the support and maintenance, we see high-cost implications."
"Synapse Analytics needs to develop an automation framework because now you have to build a cache yourself. You have to build a pipeline in WhereScape, which does end-to-end pipeline automation well. Microsoft should come up with a framework to save people time. If they developed a tool like WhereScape, it would dramatically reduce development time."
"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."
"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 Application Express and Oracle R Enterprise fully supported, and I would like to see Oracle Data Mining supported as a front end."
"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 solution could be improved by allowing for migration tools from other cloud services, including migration from Amazon Redshift, RDS, and Aurora."
"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."
"My main suggestion for Oracle is the configuration and key values that come for JSON files. When we create a table, especially if you see in our RedShift or some other stuff, if I create a table on top of a JSON file with multiple array columns or superset columns, those column values create some difficulty in Oracle."
"It is very important the integration with other platforms be made to be as easy as it is with an on-premises deployment."
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Microsoft Azure Synapse Analytics is ranked 2nd in Cloud Data Warehouse with 86 reviews while Oracle Autonomous Data Warehouse is ranked 10th in Cloud Data Warehouse with 16 reviews. Microsoft Azure Synapse Analytics is rated 7.8, while Oracle Autonomous Data Warehouse is rated 8.6. The top reviewer of Microsoft Azure Synapse Analytics writes "No competitors provide the entire solution to one place ". 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". Microsoft Azure Synapse Analytics is most compared with Azure Data Factory, SAP BW4HANA, Snowflake, Teradata and Amazon Redshift, whereas Oracle Autonomous Data Warehouse is most compared with Oracle Exadata, Snowflake, BigQuery, Amazon Redshift and Teradata. See our Microsoft Azure Synapse Analytics vs. Oracle Autonomous Data Warehouse report.
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