Microsoft Azure Synapse Analytics vs Oracle Autonomous Data Warehouse comparison

Microsoft and Oracle are both solutions in the Cloud Data Warehouse category. Microsoft is ranked #9 with an average rating of 7.7, while Oracle is ranked #14 with an average rating of 7.7. Microsoft holds a 5.7% mindshare in CDW, compared to Oracle’s 5.3% mindshare. Additionally, 94% of Microsoft users are willing to recommend the solution, compared to 95% of Oracle users who would recommend it.

Microsoft Azure Synapse Ana...

Read 98 Microsoft Azure Synapse Analytics reviews

4,927 Views
3,055 Comparison Views

94% willing to recommend

Oracle Autonomous Data Ware...

Read 19 Oracle Autonomous Data Warehouse reviews

2,432 Views
1,775 Comparison Views

95% willing to recommend

Microsoft Azure Synapse Ana...

Oracle Autonomous Data Ware...

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Executive SummaryUpdated on Dec 18, 2024

Microsoft Azure Synapse Analytics and Oracle Autonomous Data Warehouse are top contenders in the cloud data warehousing category. Oracle seems to have the upper hand with superior automation and performance features highlighted in the comparisons.

Features: Microsoft Azure Synapse Analytics is noted for its flexibility, ease of administration, and integration with Power BI. Its MPP architecture supports large-scale data processing and modern tool integration. Oracle Autonomous Data Warehouse offers self-securing, self-patching, and self-tuning capabilities, leveraging automation for tasks like indexing and adaptation. Users appreciate its scalability and Exadata-based performance.

Room for Improvement: Microsoft Azure Synapse Analytics could enhance pricing transparency, Active Directory integration, and user interfaces for non-technical users. It would benefit from Data Factory and governance improvements. Oracle Autonomous Data Warehouse should focus on improving user-friendliness, GoldenGate integration, and unstructured data handling. There's also a need for flexible pricing and better on-premises migration functionalities.

Ease of Deployment and Customer Service: Microsoft Azure Synapse Analytics is utilized in public, private, and hybrid clouds, with mixed reviews on customer service, though generally responsive. Larger customers tend to receive superior support. Oracle Autonomous Data Warehouse is praised for its technical support, known for quick responses and proactive updates. While Microsoft benefits from a broad ecosystem, Oracle offers consistent and localized support.

Pricing and ROI: Both solutions use a pay-as-you-go model. Oracle's pricing is CPU-based, allowing easy scaling, although generally higher, justified by advanced features. Azure pricing varies, with some users finding it cost-effective but unpredictable. Oracle emphasizes performance and strategic cost savings despite higher costs, while Microsoft offers flexible deployment, appealing to Azure ecosystem users.

To learn more, read our detailed Microsoft Azure Synapse Analytics vs. Oracle Autonomous Data Warehouse Report (Updated: April 2026).

Buyer's Guide

Microsoft Azure Synapse Analytics vs. Oracle Autonomous Data Warehouse

April 2026

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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

9th

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

14th

Average Rating

8.4

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of April 2026, in the Cloud Data Warehouse category, the mindshare of Microsoft Azure Synapse Analytics is 5.7%, down from 6.3% compared to the previous year. The mindshare of Oracle Autonomous Data Warehouse is 5.3%, up from 4.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Warehouse Mindshare Distribution
Product	Mindshare (%)
Microsoft Azure Synapse Analytics	5.7%
Oracle Autonomous Data Warehouse	5.3%
Other	89.0%

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.

Read full review

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 solution has helped to predict sales and focus attention on enhancements that have improved the bottom line."

"We use Azure Synapse Analytics in many different areas and industries, so I like that you can administrate and create pipelines for difference sources of data and later integrate and deploy it to other internal areas, such as separate dashboards for financials, and so on."

"Our primary use case is for gathering data and analytics, as we provide insights into vehicle data, gathering millions of records per second across millions of vehicles running in production."

"The features most valuable are the simplicity, how easy it is to create a dashboard from different information systems."

"The ability to handle large data stands out for Microsoft Azure Synapse Analytics."

"For those working in the retail sector, this product can capture all the transactional data throughout a company's stores, process them, and put them into the Azure Synapses."

"The most valuable features of Microsoft Azure Synapse Analytics are the user experience because it is easy to make analyses, load different databases, and different resources, and our end users can do the analysis by themselves without IT supervising."

"We haven't had any issues when it comes to customization."

More Microsoft Azure Synapse Analytics pros

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

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

"The product has self-repair features."

"I like the fact that the solution is self-patching, that it's running machine-learning generally across its logs all the time in order to identify any issues and to self-repair."

"The solution has a self-backup, so you don't need a DBA (database administrator) to do a backup."

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

"Oracle Autonomous Data Warehouse is used globally to deliver extreme performance on large Financial data sets."

"The solution integrates well with Power BI."

More Oracle Autonomous Data Warehouse pros

Cons

"Synapse Analytics' performance slows down if you don't get your distribution right because it gets queued and goes into a single node."

"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."

"It is difficult to configure, especially if you have multiple domains."

"More integration is needed to improve the product for the future. There needs to be more flexibility when developing applications with this product."

"This is a young product in transition to the cloud and it needs more work before it is both settled as a product and competitive in the market."

"I am very sure that there are areas in need of improvement, but I can't recall what they are off the top of my head."

"I would like to see more ready-to-use products from Synapse. Right now, everything seems a bit futuristic without much modern use."

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

More Microsoft Azure Synapse Analytics cons

"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."

"One of the major problem is creating custom tablespace."

"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."

"Ease of connectivity could be improved."

"The setup is complex."

"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."

"Sometimes the solution works differently between the cloud and on-premises. It needs to be more consistent and predictable."

"It is good as data warehouses go, but it is not that good for really big data."

More Oracle Autonomous Data Warehouse cons

Pricing and Cost Advice

"The solution is subscription-based. You can also pay to use the product as you go."

"There's no license required for Microsoft Azure Synapse Analytics. the model is more of a use-based system. You got to pay for computing power and disk storage. Everything has different units and is kept backed up. Microsoft Azure Synapse Analytics uses storage units(SU). This is how everything's computed for cost."

"It requires a less expensive version because currently, not every customer is able to buy it. If it could have a smaller setup that doesn't require so many resources, it would be helpful, and we would be able to use it in more cases. We are a small country, and most of our customers are quite small businesses."

"I would rate the ROI a nine out of ten, where one is zero value and ten is 100% value."

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

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

"You have to be very careful with one specific service inside Microsoft Azure Synapse Analytics which is called the Sequel Data Warehouse Dedicated. It is very reliable and performs well, but it's expensive. You need to define the tier well because you can choose between several tiers and you have to define which suits your needs and not overperform the tier because it's quite expensive."

"The computer and storage costs are totally separate which allows you to work independently or manage costs."

More Microsoft Azure Synapse Analytics pricing and cost advice

"The licensing cost of the product can vary since you can integrate it very easily with other products or other cloud products...You pay as you use it, so it is not yearly or monthly payments to be made toward Oracle."

"The solution's cost is reasonable."

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

"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."

"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."

"The price depends on the configuration we choose."

"ROI is high."

More Oracle Autonomous Data Warehouse pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

12%

Manufacturing Company

10%

Comms Service Provider

Government

Manufacturing Company

Media Company

Computer Software Company

Financial Services Firm

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	29
Midsize Enterprise	18
Large Enterprise	56

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...

See all answers

What do you like most about Microsoft Azure Synapse Analytics?

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

See all answers

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

I think the licensing cost for Microsoft Azure Synapse Analytics is very high, but I have a local system to support that, so I don't consider that in the near future.

See all answers

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.

See all answers

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.

See all answers

What is your primary use case for Oracle Autonomous Data Warehouse?

We are using Oracle Autonomous Data Warehouse for analytics in my company.

See all answers

Comparisons

Snowflake vs Microsoft Azure Synapse Analytics

Compared 18% of the time

Amazon Redshift vs Microsoft Azure Synapse Analytics

Compared 7% of the time

Azure Data Factory vs Microsoft Azure Synapse Analytics

Compared 5% of the time

Teradata vs Microsoft Azure Synapse Analytics

Compared 5% of the time

Oracle Exadata vs Microsoft Azure Synapse Analytics

Compared 4% of the time

More Microsoft Azure Synapse Analytics Competitors

BigQuery vs Oracle Autonomous Data Warehouse

Compared 22% of the time

Snowflake vs Oracle Autonomous Data Warehouse

Compared 17% of the time

Databricks vs Oracle Autonomous Data Warehouse

Compared 12% of the time

Amazon Redshift vs Oracle Autonomous Data Warehouse

Compared 5% of the time

Oracle Exadata vs Oracle Autonomous Data Warehouse

Compared 5% of the time

More Oracle Autonomous Data Warehouse Competitors

Product Reports

Buyer's Guide

Microsoft Azure Synapse Analytics

March 2026

Microsoft Azure Synapse Analytics report

Download Microsoft Azure Synapse Analytics product report

Buyer's Guide

Oracle Autonomous Data Warehouse

March 2026

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

Buyer's Guide

Microsoft Azure Synapse Analytics vs. Oracle Autonomous Data Warehouse

April 2026

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Find out what your peers are saying about Microsoft Azure Synapse Analytics vs. Oracle Autonomous Data Warehouse and other solutions. Updated: April 2026.

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