Microsoft Azure Synapse Analytics vs Oracle Autonomous Data Warehouse comparison

Why PeerSpot?

Microsoft and Oracle are both solutions in the Cloud Data Warehouse category. Microsoft is ranked #6 with an average rating of 7.3, while Oracle is ranked #14 with an average rating of 6.0. Microsoft holds a 6.1% mindshare in CDW, compared to Oracle’s 4.1% 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

8,610 Views
5,683 Comparison Views

94% willing to recommend

Oracle Autonomous Data Ware...

Read 19 Oracle Autonomous Data Warehouse reviews

3,863 Views
2,781 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: September 2026).

Buyer's Guide

Microsoft Azure Synapse Analytics vs. Oracle Autonomous Data Warehouse

September 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

6th

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 November 2026, in the Cloud Data Warehouse category, the mindshare of Microsoft Azure Synapse Analytics is 6.1%, down from 6.5% compared to the previous year. The mindshare of Oracle Autonomous Data Warehouse is 4.1%, down from 5.3% 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	6.1%
Oracle Autonomous Data Warehouse	4.1%
Other	89.8%

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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reviewer1297710

IT Administrator at a manufacturing company with 1,001-5,000 employees

Analytics and data security needs are met but optimization requires improvement

We are using Oracle Autonomous Data Warehouse for analytics in my company The solution is used for analytics and it works for our data security needs. We continue to use it with satisfaction. Optimization should be better. The SQLs are sometimes very slow. I also noticed that Java is not…

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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

"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 architecture, including compute and storage, is good."

"The speed is great and the architecture is excellent."

"The most valuable features are the flexibility and that it's easy to use as an end-user compared to AWS."

"What I found most valuable in Microsoft Azure Synapse Analytics is that it's native only for Azure, so you get better performance and there's no issue."

"The most valuable feature of the solution is the analytics and that it can connect with Power BI."

"The whole solution is interesting for us."

"One of the most valuable features of this solution is its ability to integrate well with other services offered by Azure."

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."

"Amazing performance, it is a revolution."

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

"The product has self-repair features."

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

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

"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."

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

More Oracle Autonomous Data Warehouse pros

Cons

"Microsoft Azure Synapse Analytics's overall integration within the Azure ecosystem could improve. The native Microsoft solution versus another solution, such as Databricks, there are areas where there could be some improvements."

"In our company, we always want to improve our data management, including how to manage structured and unstructured data."

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

"If I'm looking for something good in the cloud, I would want it to have better standard connectors."

"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 can get expensive, and it's hard to monitor the costs."

"One area that could be improved is the schema management."

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

More Microsoft Azure Synapse Analytics cons

"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."

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

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

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

"Ease of connectivity could be improved."

"The solution lacks visibility options."

"The solution could be improved by allowing for migration tools from other cloud services, including migration from Amazon Redshift, RDS, and Aurora."

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

More Oracle Autonomous Data Warehouse cons

Pricing and Cost Advice

"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."

"We chose the serverless option for the database which has saved us a lot of money. Our costs are approximately £600 per month."

"They are cost aggressive, and it integrates well with other Microsoft tools."

"Microsoft Azure Synapse Analytics is a moderately priced solution."

"Its price could be better. It was a school project, and I got it for free. If I try to pay through my company, it is a little bit more expensive as compared to Oracle."

"I think Microsoft Azure Synapse Analytics is priced well, and I would rate the price at eight out of ten."

"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."

"There is a cost calculator available online that allows you to input your entire scenario, and it will get back to you with information on what the costs are going to be."

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."

"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."

"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."

"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."

"The solution is expensive."

"The cost is perfect with Oracle Universal credit."

More Oracle Autonomous Data Warehouse pricing and cost advice

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Top Industries

By visitors reading reviews

Outsourcing Company

12%

Financial Services Firm

12%

Manufacturing Company

Construction Company

Financial Services Firm

12%

Media Company

10%

Manufacturing Company

Outsourcing Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	28
Midsize Enterprise	18
Large Enterprise	60

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 20% of the time

Amazon Redshift vs Microsoft Azure Synapse Analytics

Compared 8% of the time

Azure Data Factory vs Microsoft Azure Synapse Analytics

Compared 6% of the time

SAP BW4HANA vs Microsoft Azure Synapse Analytics

Compared 6% of the time

Oracle Exadata vs Microsoft Azure Synapse Analytics

Compared 5% of the time

More Microsoft Azure Synapse Analytics Competitors

Snowflake vs Oracle Autonomous Data Warehouse

Compared 17% of the time

BigQuery vs Oracle Autonomous Data Warehouse

Compared 13% of the time

Databricks vs Oracle Autonomous Data Warehouse

Compared 8% of the time

VMware Tanzu Data Solutions vs Oracle Autonomous Data Warehouse

Compared 8% 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

October 2026

Microsoft Azure Synapse Analytics report

Download Microsoft Azure Synapse Analytics product report

Buyer's Guide

Oracle Autonomous Data Warehouse

October 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

September 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: September 2026.

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