Microsoft Azure Synapse Analytics vs Oracle Autonomous Data Warehouse comparison

Microsoft Azure Synapse Analytics vs. Oracle Autonomous Data Warehouse

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Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

Microsoft Azure Synapse Ana...

Ranking in Cloud Data Warehouse

5th

Average Rating

7.8

Reviews Sentiment

6.8

Number of Reviews

Ranking in other categories

No ranking in other categories

Oracle Autonomous Data Ware...

Ranking in Cloud Data Warehouse

12th

Average Rating

8.4

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of October 2025, in the Cloud Data Warehouse category, the mindshare of Microsoft Azure Synapse Analytics is 6.3%, down from 7.5% compared to the previous year. The mindshare of Oracle Autonomous Data Warehouse is 5.2%, up from 4.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Warehouse Market Share Distribution
Product	Market Share (%)
Microsoft Azure Synapse Analytics	6.3%
Oracle Autonomous Data Warehouse	5.2%
Other	88.5%

Cloud Data Warehouse

Featured Reviews

AnandTiwari

CTO at New Turn Technologies

Has consistently supported integration across diverse environments and streamlined deployment processes

Microsoft Azure Synapse Analytics could improve their pricing structure. They currently have two separate pricing tiers: full log and partial log. I suggest they implement a single price and reduce charges on logs. They could implement a cap with some free tier or price tier based on the GBs of log collected. This would help customers use Azure more effectively. Microsoft Azure Synapse Analytics is an excellent product because it includes both SIEM and orchestration capabilities with playbooks, but the log management part is very costly. Regarding future improvements, I would appreciate more application connectors for integration, particularly for on-premise based solutions. Many customers still maintain on-premise infrastructure, so having more integration possibilities for these environments would be beneficial.

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Kwajah Mohiuddin

Global Head of Architecture at a financial services firm with 1,001-5,000 employees

Provides self-repair features, but the setup is complex

We use the product for online applications. We use it in the financial industry The product has self-repair features. The tool tunes itself. It separates compute from storage. We can scale storage and compute separately. The setup is complex. Oracle is a complex tool. I have been using Oracle…

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"The most valuable features of Microsoft Azure Synapse Analytics are how easy and quick it is to set up the linked services."

"Fills the gap between big data and classic data warehouses."

"The solution's scalability is very, very good. It's one of the most important aspects for us."

"The biggest benefits are scalability and ease of use when looking at performance tuning and optimization."

"They are available on the Cloud, and the platform is very intuitive."

"The stability is pretty good."

"Our primary use case is for gathering data and analytics. We provide insights into vehicle data. We gather millions of records per second and we have various millions of vehicles running across."

"The features I find most valuable in Microsoft Azure Synapse Analytics are comprehensive because they have combined almost five to six components into one single bundle."

More Microsoft Azure Synapse Analytics pros

"One advantage is that if you already have an Oracle Database, it easily integrates with that."

"The product is easy to use."

"The performance and scalability are awesome."

"The solution is self-securing. All data is encrypted and security updates and patches are applied automatically both periodically and off-cycle."

"I loved the simplicity of loading the data and simply relying on the self-tuning capabilities of ADW."

"I really like the auto-tuning, auto-scaling, and the automatic load balancing and query tuning in the system."

"A very good integration feature that restricts access to unauthorized people."

"The solution is used for analytics and it works for our data security needs."

More Oracle Autonomous Data Warehouse pros

Cons

"Unfortunately, we have had some issues with the dashboard reporting. Sometimes, the data for specific periods would just appear blank on the dashboard. To investigate this, we worked with a Microsoft incident agent and it turned out to be a result of bugs in the platform when dealing with specific types of queries in Azure Data Factory."

"The macro functions, though useful, are not totally user-friendly. Some people have difficulties in learning them."

"It's pay as you go, so you never know what your bill is going to be beforehand, and that's scary for customers. If you have someone who makes a mistake and the program's a loop that is running all night, you could receive a very expensive bill."

"It could be more stable."

"One potential area for improvement could be the availability of an on-premises data lake implementation, as the product is currently only implemented in a cloud environment."

"Microsoft Azure Synapse Analytics can improve by increasing the size of the files that we can load on the platform. We have some files that are too large to be loaded and it would be a benefit to us if the limit was increased. Additionally, the way we use the tool for generating reports can be made better. They should add some drag-and-drop rules without the need of programming these rules using some programming language. It would be helpful if we did not need someone that was technically advanced to be able to do it with, such as someone with no IT background. Having a reporting tool without code would be great."

"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."

"The solution should offer a serverless model like Snowflake."

More Microsoft Azure Synapse Analytics cons

"I would like to see an on-premise solution in the future."

"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."

"The setup is complex."

"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."

"A lot of the tools that were previously there have now been taken away."

"The solution lacks visibility options."

"The installation process is complex. Oracle can make the installation process better."

"Oracle Autonomous Data Warehouse is not available as an on-premises solution."

More Oracle Autonomous Data Warehouse cons

Pricing and Cost Advice

"The pricing is okay. You can pay as you go."

"Very costly solution and other products are available for less."

"I understand that Synapse Analytics' pricing is lower than Informatica's."

"Microsoft Azure Synapse Analytics is an expensive solution and there is a license needed to use it. My company has an enterprise license."

"The solution is expensive at the enterprise level."

"This solution starts at €1000.00 a month for just the basics and can go up to €300,000.00 per month for the fastest version."

"It just depends on how big your instance is. It could be anywhere from 1,000 to 50,000 per year depending on how big your instance is. You pay based on how big you make your database. Essentially, they charge you per hour of usage."

"The price of the package not expensive and depends on how much it is used."

More Microsoft Azure Synapse Analytics pricing and cost advice

"We pay approximately $70,000 per month. The cost includes maintenance and support."

"The cost is perfect with Oracle Universal credit."

"Oracle Autonomous Data Warehouse's pricing is fair and reasonable compared to the other cloud vendors."

"Cloud solutions are cheaper, but in the long run, they may not be much cheaper. They certainly have a lower initial cost. The licensing is yearly, and it is based on the size of the hardware and the number of users."

"You pay as you go, and you don't pay for services that you don't use."

"On a scale from one to ten, where one is a low price and ten is a high price, I rate the pricing an eight."

"The solution's cost is reasonable."

"In terms of architecture and pricing structure, I feel it is a little bit costly compared to Azure. It's fine compared to RedShift, but compared to Azure, it's a bit pricey when you calculate for one TB storage plus around five hours of reporting with the frequency of 1TB data. The cost adds up, making Oracle a bit expensive."

More Oracle Autonomous Data Warehouse pricing and cost advice

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Top Industries

By visitors reading reviews

Manufacturing Company

12%

Financial Services Firm

Computer Software Company

Government

Computer Software Company

10%

Manufacturing Company

University

Insurance Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	29
Midsize Enterprise	18
Large Enterprise	55

By reviewers
Company Size	Count
Small Business	7
Midsize Enterprise	1
Large Enterprise	11

Questions from the Community

How does Amazon Redshift compare with Microsoft Azure Synapse Analytics?

Amazon Redshift is very fast, has a very good response time, and is very user-friendly. The initial setup is very straightforward. This solution can merge and integrate well with many different dat...

What do you like most about Microsoft Azure Synapse Analytics?

The product is easy to use, and anybody can easily migrate to advanced DB.

What is your experience regarding pricing and costs for Microsoft Azure Synapse Analytics?

I find the pricing of Microsoft Azure Synapse Analytics reasonable; compared to AWS Glue or Databricks, it is reasonable.

What do you like most about Oracle Autonomous Data Warehouse?

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...

What is your experience regarding pricing and costs for Oracle Autonomous Data Warehouse?

We pay approximately $70,000 per month. The cost includes maintenance and support.

What needs improvement with Oracle Autonomous Data Warehouse?

Optimization should be better. The SQLs are sometimes very slow. I also noticed that Java is not supported, which is not ideal.

Snowflake vs Microsoft Azure Synapse Analytics

Comparisons

Compared 18% of the time

Amazon Redshift vs Microsoft Azure Synapse Analytics

Compared 11% of the time

SAP BW4HANA vs Microsoft Azure Synapse Analytics

Compared 7% of the time

Teradata vs Microsoft Azure Synapse Analytics

Compared 6% of the time

Azure Data Factory vs Microsoft Azure Synapse Analytics

Compared 6% of the time

More Microsoft Azure Synapse Analytics Competitors

BigQuery vs Oracle Autonomous Data Warehouse

Compared 31% of the time

Snowflake vs Oracle Autonomous Data Warehouse

Compared 13% of the time

Oracle Exadata vs Oracle Autonomous Data Warehouse

Compared 10% of the time

Databricks vs Oracle Autonomous Data Warehouse

Compared 9% of the time

OpenText Analytics Database (Vertica) vs Oracle Autonomous Data Warehouse

Compared 6% of the time

More Oracle Autonomous Data Warehouse Competitors

Product Reports

Microsoft Azure Synapse Analytics

Download Microsoft Azure Synapse Analytics product report

Microsoft Azure Synapse Analytics report

Oracle Autonomous Data Warehouse

Download Oracle Autonomous Data Warehouse product report

Also Known As

Azure Synapse Analytics, Microsoft Azure SQL Data Warehouse, Microsoft Azure SQL DW, Azure SQL Data Warehouse, MS Azure Synapse Analytics

No data available

Overview

Microsoft Azure Synapse Analytics is an end-to-end analytics solution that successfully combines analytical services to merge big data analytics and enterprise data warehouses into a single unified platform. The solution can run intelligent distributed queries among nodes, and provides the ability to query both relational and non-relational data.

Microsoft Azure Synapse Analytics is built with these 4 components:

Synapse SQL
Spark
Synapse Pipeline
Studio

Microsoft Azure Synapse Analytics Features

Microsoft Azure Synapse Analytics has many valuable key features, including:

Cloud Data Service: WIth Microsoft Azure Synapse Analytics you can operate services (data analytics, machine learning, data warehousing, dashboarding, etc.) in a single workspace via the cloud.
Structured and unstructured data: Microsoft Azure Synapse Analytics supports both structured and unstructured data and allows you to manage relational and non-relational data - unlike data warehouses and lakes that tend to store them respectively.
Effective data storage: Microsoft Azure Synapse Analytics offers next-level data storage with high availability and different tiers.
Responsive data engine: Microsoft Azure Synapse Analytics uses Massive Parallel Processing (MPP) and is designed to handle large volumes of data and analytical workloads efficiently without any problems.
Several scripting languages: The solution provides language compatibility and supports different programming languages, such as Python, Java, Spark SQL, and Scala.
Query optimization: Microsoft Azure Synapse Analytics works well to facilitate limitless concurrency and performance optimization. It also simplifies workload management.

Microsoft Azure Synapse Analytics Benefits

Some of the benefits of using Microsoft Azure Synapse Analytics include:

Database templates: Microsoft Azure Synapse Analytics offers industry-specific database templates that make it easy to combine and shape data.
Better business insights: With Microsoft Azure Synapse Analytics you can expand discovery of insights from all your data and apply machine learning models to all your intelligent apps.
Reduce project development time: Microsoft Azure Synapse Analytics makes it possible to have a unified experience for developing end-to-end analytics, which reduces project development time significantly.
Eliminate data barriers: By using Microsoft Azure Synapse Analytics, you can perform analytics on operational and business apps data without data movement.
Advanced security: Microsoft Azure Synapse Analytics provides both advanced security and privacy features to ensure data protection.
Machine Learning: Microsoft Azure Synapse Analytics integrates Azure Machine Learning, Azure Cognitive Services, and Power BI.

Reviews from Real Users

Below are some reviews and helpful feedback written by Microsoft Azure Synapse Analytics users who are currently using the solution.

PeerSpot user Jael S., who is an Information Architect at Systems Analysis & Design Engineering, comments on her experience using the product, saying that it is “Scalable, intuitive, facilitates compliance and keeps your data secure”. She also says "We also like governance. It looks at what the requirements are for the company to identify the best way to ensure compliance is met when you move to the cloud."

Michel T., CHTO at Timp-iT, mentions that "the features most valuable are the simplicity, how easy it is to create a dashboard from different information systems."

A Senior Teradata Consultant at a tech services company says, "Microsoft provides both the platform and the data center, so you don't have to look for a cloud vendor. It saves you from having to deal with two vendors for the same task."

Microsoft

Oracle Autonomous Data Warehouse is the world’s first and only autonomous database optimized for analytic workloads, including data marts, data warehouses, data lakes, and data lakehouses. With Autonomous Data Warehouse, data scientists, business analysts, and nonexperts can rapidly, easily, and cost-effectively discover business insights using data of any size and type. Built for the cloud and optimized using Oracle Exadata, Autonomous Data Warehouse benefits from faster performance and, according to an IDC report (PDF), lowers operational costs by an average of 63%.

Autonomous Database provides the foundation for a data lakehouse—a modern, open architecture that enables you to store, analyze, and understand all your data. The data lakehouse combines the power and richness of data warehouses with the breadth, flexibility, and low cost of popular open source data lake technologies. Access your data lakehouse through Autonomous Database using the world's most powerful and open SQL processing engine.

Oracle

Sample Customers

Toshiba, Carnival, LG Electronics, Jet.com, Adobe,

Hertz, TaylorMade Golf, Outront Media, Kingold, FSmart, Drop-Tank

Microsoft Azure Synapse Analytics vs. Oracle Autonomous Data Warehouse