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 #5 with an average rating of 7.7, while Oracle is ranked #13 with an average rating of 7.7. Microsoft holds a 5.8% mindshare in CDW, compared to Oracle’s 4.6% 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

6,459 Views
4,198 Comparison Views

94% willing to recommend

Oracle Autonomous Data Ware...

Read 19 Oracle Autonomous Data Warehouse reviews

3,036 Views
2,247 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: June 2026).

Buyer's Guide

Microsoft Azure Synapse Analytics vs. Oracle Autonomous Data Warehouse

June 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

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

13th

Average Rating

8.4

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of July 2026, in the Cloud Data Warehouse category, the mindshare of Microsoft Azure Synapse Analytics is 5.8%, down from 6.0% compared to the previous year. The mindshare of Oracle Autonomous Data Warehouse is 4.6%, down from 4.9% 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	5.8%
Oracle Autonomous Data Warehouse	4.6%
Other	89.6%

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

"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."

"Compared to hosting a Microsoft setup on premise, if you use Azure Synapse, the return on investment is very high because you get rid of your hardware and licensing, move to a subscription-based pay-as-you-use model, reduce operational costs, optimize more, diminish capital expenditure by moving to an OpEx model, and simplify overall management."

"The most valuable feature of this solution is its filling of the gap between big data and classic data warehouses."

"The solution operates like a typical SQL Server environment so there is no alienation in terms of technical knowledge."

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

"The most important feature for me is the integration with PolyBase."

"Synapse makes it easy to integrate and onboard data from other Microsoft and Azure sources. The interface is familiar because we were using Azure Data Factory before Synapse. It made the transition even easier because the Synapse interface is exactly the same."

"The stability of the solution is pretty good."

More Microsoft Azure Synapse Analytics pros

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

"The autonomous database provides several benefits and unmatched performance."

"The analytics have been very good. We've found them to be quite useful."

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

"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."

"It provides Transparent Data Encryption (TDE) capabilities by default to address data security issues."

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

"The integration feature is very good because you can automate protection security automatically, restricting the access of unauthorized people."

More Oracle Autonomous Data Warehouse pros

Cons

"Synapse Analytics needs to develop an automation framework because now you have to build a cache yourself."

"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."

"Documentation could be improved."

"Real-time integration is hard to do in Microsoft Azure Synapse Analytics."

"We'd, of course, always like to pay less for the service if we can."

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

"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."

"Comes with a pretty steep learning curve."

More Microsoft Azure Synapse Analytics cons

"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."

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

"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."

"Optimization should be better."

"The setup is complex."

"Oracle should increase visibility options because what's available now is limited."

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

More Oracle Autonomous Data Warehouse cons

Pricing and Cost Advice

"The solution is expensive at the enterprise level."

"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."

"We only have to pay for what we use in the solution. It's easy for the customers. It's not more than some companies, not more than 300 to 400 users. They do not need to buy other license products, such as SAP B1, or analytics tools in the market, such as Tableau."

"I'm not sure of the exact cost, however, it is around $100,000 a year."

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

"The price of this solution could be improved."

"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."

"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."

More Microsoft Azure Synapse Analytics pricing and cost advice

"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."

"The solution is expensive."

"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."

"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 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

11%

Manufacturing Company

Construction Company

Outsourcing Company

Manufacturing Company

10%

Media Company

Financial Services Firm

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	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 19% of the time

Amazon Redshift vs Microsoft Azure Synapse Analytics

Compared 9% of the time

Azure Data Factory vs Microsoft Azure Synapse Analytics

Compared 6% of the time

BigQuery vs Microsoft Azure Synapse Analytics

Compared 5% of the time

SAP BW4HANA vs Microsoft Azure Synapse Analytics

Compared 5% of the time

More Microsoft Azure Synapse Analytics Competitors

BigQuery vs Oracle Autonomous Data Warehouse

Compared 17% of the time

Snowflake vs Oracle Autonomous Data Warehouse

Compared 16% of the time

Databricks vs Oracle Autonomous Data Warehouse

Compared 9% of the time

Amazon Redshift vs Oracle Autonomous Data Warehouse

Compared 6% of the time

VMware Tanzu Data Solutions vs Oracle Autonomous Data Warehouse

Compared 6% of the time

More Oracle Autonomous Data Warehouse Competitors

Product Reports

Buyer's Guide

Microsoft Azure Synapse Analytics

July 2026

Microsoft Azure Synapse Analytics report

Download Microsoft Azure Synapse Analytics product report

Buyer's Guide

Oracle Autonomous Data Warehouse

July 2026

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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

June 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: June 2026.

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