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 #7 with an average rating of 7.7, while Oracle is ranked #14 with an average rating of 7.7. Microsoft holds a 5.6% mindshare in CDW, compared to Oracle’s 5.0% 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

5,492 Views
3,460 Comparison Views

94% willing to recommend

Oracle Autonomous Data Ware...

Read 19 Oracle Autonomous Data Warehouse reviews

2,645 Views
1,931 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

7th

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 May 2026, in the Cloud Data Warehouse category, the mindshare of Microsoft Azure Synapse Analytics is 5.6%, down from 6.2% compared to the previous year. The mindshare of Oracle Autonomous Data Warehouse is 5.0%, up from 4.6% 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	5.6%
Oracle Autonomous Data Warehouse	5.0%
Other	89.4%

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 solution offers strong scalability opportunities."

"The most valuable feature is the incremental load because we do not need to refresh the entire data on a daily basis."

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

"This is a stable solution with many functionalities."

"Microsoft Azure uses the Massively Parallel Processing concept for data warehousing, the speed is great and the architecture is excellent."

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

"The solution's scalability is very, very good; it's widely acknowledged as an excellent product throughout the industry, and there is a lot of knowledge about it in the Netherlands, making it very easy to find consultancy and employees who can help us with its modern architecture."

"Synapse Analytics' best feature is its ability to process large files."

More Microsoft Azure Synapse Analytics pros

"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."

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

"It is an extremely scalable solution since you can dynamically change the resources as some other cloud solutions."

"The product is easy to use."

"I highly recommend it for companies who want to test their application functionality, dev, or test DBs for cost optimization."

"It is a very stable tool...It is an extremely scalable tool."

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

More Oracle Autonomous Data Warehouse pros

Cons

"I'm not entirely happy with the billing model. I'm not entirely happy with how the enterprise services are pretty expensive, but that's about it."

"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."

"Some of the best-in-class ETL products that are available in the market, such as Informatica ETL, are far more mature than this solution."

"In the last six months, there have been a couple of incidents. We have experienced some outages."

"Microsoft Azure Synapse Analytics could improve the section in the solution where you can implement the Python Spark pipelines, it's not the same as in Databricks which would be better."

"While the solution is flexible, sometimes this works against the user."

"Integration with other products is an area that can be improved."

"The initial setup has a bit of a learning curve."

More Microsoft Azure Synapse Analytics cons

"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."

"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 initial setup was pretty complex. It was not easy."

"We are not satisfied with the technical support. Their understanding is lacking."

"It is very important the integration with other platforms be made to be as easy as it is with an on-premises deployment."

"The solution lacks visibility options."

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

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

More Oracle Autonomous Data Warehouse cons

Pricing and Cost Advice

"Because it's cloud the cost is a different convention and the licensing costs are not the same."

"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."

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

"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."

"It goes by the usage, and there are some limits. Synapse goes by particular pricing, and it is expensive. Both Azure Synapse Analytics and Snowflake are pretty expensive. They don't have standard pricing. They deal with each customer differently."

"We normally pay between $300 and $500 per month, which is quite expensive for how much we actually use it, performance- and usage-wise. They have a cheap version and an expensive version, and our usage usually falls in the middle ground, which makes it not as cost-effective as it could be."

"Price is dependent of the use case of the customer. Customers are not likely to only use this as an individual platform/database, they are likely to bundle it with the Azure stack."

"The product is expensive."

More Microsoft Azure Synapse Analytics pricing and cost advice

"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."

"The price depends on the configuration we choose."

"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 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 cost is perfect with Oracle Universal credit."

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

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

"The solution's cost is reasonable."

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

Comms Service Provider

Government

Manufacturing Company

10%

Media Company

Insurance 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	59

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 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 needs improvement with Microsoft Azure Synapse Analytics?

I am hoping that in the future Microsoft Azure Synapse Analytics may have AI support.

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 6% of the time

Oracle Exadata vs Microsoft Azure Synapse Analytics

Compared 5% of the time

BigQuery vs Microsoft Azure Synapse Analytics

Compared 4% of the time

More Microsoft Azure Synapse Analytics Competitors

BigQuery vs Oracle Autonomous Data Warehouse

Compared 19% of the time

Snowflake vs Oracle Autonomous Data Warehouse

Compared 17% of the time

Databricks vs Oracle Autonomous Data Warehouse

Compared 10% of the time

Amazon Redshift vs Oracle Autonomous Data Warehouse

Compared 5% of the time

Snowflake Analytics 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

May 2026

Microsoft Azure Synapse Analytics report

Download Microsoft Azure Synapse Analytics product report

Buyer's Guide

Oracle Autonomous Data Warehouse

May 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 integrates data warehousing and big data analytics seamlessly. It provides scalability and user-friendly features for efficient, real-time reporting and data management.

Azure Synapse Analytics is designed for seamless data integration, allowing users to scale their operations effectively while providing extensive analytics capabilities. It supports both traditional data warehousing and big data solutions with real-time reporting through an interactive interface that integrates well with Power BI. The platform's serverless flexibility optimizes cost while ensuring robust security, leveraging users' familiarity with SQL technologies. Scalability allows processing of large datasets efficiently, empowering companies to connect disparate data sources and support industry-specific needs. Despite its strengths, Synapse users often seek improved governance, schema management, and technical support. Enhanced integration with Microsoft and third-party tools, along with better data loading capabilities, are also desired.

What are the key features of Microsoft Azure Synapse Analytics?

SQL Pooling: Provides a dedicated SQL pool for scalable data processing.
Massively Parallel Processing: Architecture that enhances efficiency for big data workloads.
Pipelines: Streamlines data orchestration and workflow automation.
Real-Time Reporting: Delivers quick insights by processing data in real time.
Power BI Integration: Seamlessly connects with Power BI for advanced data visualization.
Serverless Flexibility: Optimizes cost management by allowing on-demand resources.

What benefits and ROI should be considered in reviews of Microsoft Azure Synapse Analytics?

Scalability: Efficiently handles expanding data loads.
Cost Management: Serverless architecture provides cost-efficient resource usage.
Security Features: Ensures data protection and compliance.
Data Integration: Connects various data sources for unified analytics.
SQL Familiarity: Leverages common SQL skills for ease of use.

Azure Synapse Analytics is extensively implemented across sectors like healthcare, finance, marketing, and government. Organizations use it to build data pipelines, perform analytics modeling, and facilitate reporting. It supports data transformation, migration, and orchestration, enhancing business intelligence and decision-making capabilities by efficiently handling big data and connecting disparate data sources.

Microsoft

Oracle Autonomous Data Warehouse is a cloud-based service offering advanced data management capabilities, including automated administration and high performance for analytics tasks. It is ideal for enterprises prioritizing security, easy maintenance, and dynamic scale.

Oracle Autonomous Data Warehouse stands out by offering self-managing capabilities that minimize administrative overhead, allowing organizations to focus on data-driven decision-making. With features such as transparent data encryption, seamless cloud integration, and automated query tuning, it ensures secure and efficient data operations. Its architecture separates compute and storage, enhancing scalability and performance. Despite its setup complexity and higher cost than some competitors, it offers deep integration with Oracle Database, ensuring reliable performance and fast data exchange.

What features define Oracle Autonomous Data Warehouse?

Self-Patching: Automatically updates to ensure security and performance.
Auto-Scaling: Dynamically adjusts resources to meet workload demands.
Query Tuning: Optimizes queries for better performance without user intervention.
Seamless Cloud Integration: Easily connects with Oracle and other cloud applications.
Transparent Data Encryption: Provides secure data handling to meet compliance needs.
Smart Scan: Efficiently processes queries to reduce data retrieval times.

What benefits can be expected from Oracle Autonomous Data Warehouse?

Cost-Effectiveness: Reduces operational costs through automation and serverless operations.
High Security: Ensures data protection with encryption and isolated resources.
Performance Enhancement: High-speed data processing and query response times.
Easy Maintenance: Minimal administrative tasks due to automation.
Scalability: Effortlessly scales resources to accommodate growth.

Oracle Autonomous Data Warehouse is widely used in finance, banking, transport, and manufacturing, supporting data analytics in financial systems, procurement, and student management. It facilitates large-scale transaction processing, offering centralized reporting and dynamic resource allocation, which is crucial for enhancing performance across industries.

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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