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 #7 with an average rating of 7.3, while Oracle is ranked #14 with an average rating of 6.0. Microsoft holds a 6.2% mindshare in CDW, compared to Oracle’s 4.2% 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

8,092 Views
5,422 Comparison Views

94% willing to recommend

Oracle Autonomous Data Ware...

Read 19 Oracle Autonomous Data Warehouse reviews

3,631 Views
2,651 Comparison Views

95% willing to recommend

Microsoft Azure Synapse Ana...

Oracle Autonomous Data Ware...

Comparison Buyer's Guide

Download the report

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

Download the complete report

Helped 919,809 peers since 2012

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 October 2026, in the Cloud Data Warehouse category, the mindshare of Microsoft Azure Synapse Analytics is 6.2%, down from 6.3% compared to the previous year. The mindshare of Oracle Autonomous Data Warehouse is 4.2%, down from 5.1% 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	6.2%
Oracle Autonomous Data Warehouse	4.2%
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.

Read full review

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…

Read full review

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 feature of this solution is the ease of administration."

"From my point of view from what we have implemented recently, I'm happy with the solution, I'm happy with the performance."

"The solution is scalable."

"We've had a good experience with technical support in general."

"I like that the overall deployment and integration is pretty fast and then you also have virtualization to Power BI so it's also quite cost-effective."

"One of the most valuable features in Microsoft Azure Synapse Analytics is the ability to write your own ETL code using Azure Data Factory, which is a component within Synapse."

"I have been working with Microsoft, and they have been very helpful."

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

More Microsoft Azure Synapse Analytics pros

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

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

"It is a stable and scalable solution."

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

"The solution integrates well with Power BI."

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

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

"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."

More Oracle Autonomous Data Warehouse pros

Cons

"The configuration for things like high-availability could be more user-friendly for non-technical users."

"Managing workloads and data transformation using Databricks should be a focus."

"The initial setup process needs improvement. When you're moving to the cloud it takes a bit of time. It would be great if they could implement something that would make it faster."

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

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

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

"The only concern for us is the cost part. When it comes to the implementation and the support and maintenance, we see high-cost implications."

"Right now, we are really struggling with the performance. it's not as good as we had hoped."

More Microsoft Azure Synapse Analytics cons

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

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

"Ease of interconnectivity could be improved by which I mean setting up the VPN access and the like from on-premises to cloud."

"The solution lacks visibility options."

"They should make the solution more user-friendly."

"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."

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

"My main suggestion for Oracle is the configuration and key values that come for JSON files. When we create a table, especially if you see in our RedShift or some other stuff, if I create a table on top of a JSON file with multiple array columns or superset columns, those column values create some difficulty in Oracle."

More Oracle Autonomous Data Warehouse cons

Pricing and Cost Advice

"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."

"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 have a licensing cost to pay."

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

"The cost of the licensing depends on the size of the warehouse, where the cost of storage is approximately $130 USD per terabyte."

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

"Our license is very expensive"

"When we are not using this solution we can simply shut it down saving us costs, which is a nice advantage."

More Microsoft Azure Synapse Analytics pricing and cost advice

"ROI is high."

"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 price depends on the configuration we choose."

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

"The solution's cost is reasonable."

"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."

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

"The cost is perfect with Oracle Universal credit."

More Oracle Autonomous Data Warehouse pricing and cost advice

See which vendors are best for you

Use our free recommendation engine to learn which Cloud Data Warehouse solutions are best for your needs.

See recommendations

919,809 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Outsourcing Company

12%

Financial Services Firm

12%

Manufacturing Company

Construction Company

Financial Services Firm

12%

Media Company

10%

Outsourcing Company

Manufacturing 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 19% 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 12% of the time

Databricks vs Oracle Autonomous Data Warehouse

Compared 8% of the time

VMware Tanzu Data Solutions vs Oracle Autonomous Data Warehouse

Compared 7% of the time

Amazon Redshift 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

Free Report: Microsoft Azure Synapse Analytics vs. Oracle Autonomous Data Warehouse

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

DOWNLOAD NOW

919,809 professionals have used our research since 2012.

See our Microsoft Azure Synapse Analytics vs. Oracle Autonomous Data Warehouse report.

See our list of best Cloud Data Warehouse vendors.

We monitor all Cloud Data Warehouse reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.