Microsoft Azure Synapse Analytics vs Oracle Autonomous Data Warehouse comparison

Microsoft Azure Synapse Analytics vs. Oracle Autonomous Data Warehouse

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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.

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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 ability to scale out services on-demand and scale them down when they are not required is most valuable. You are in control of your expenditures, and you are also in control of the horsepower that you need. That's a major advantage."

"Its seamless integration with Azure services is most valuable. If somebody wants to use all Azure services, it is the best solution."

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

"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. Our end users can do the analysis by themselves without IT supervising. This is a great aspect of the solution, it's better for our environment."

"The most valuable feature of Microsoft Azure Synapse Analytics is its integration with the new legacy systems. Whatever application we want to integrate, we receive the reports based on the objects. The solution is easy to purchase from the cloud."

"One of the reasons we decided to go with Azure was because we knew we could scale out and we were happy with this scalability before we committed to the product."

"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."

"Scalability is built in; if you're working with a terabyte of data on one day, you can go up to a petabyte the next day, so there's no need to worry about scalability in terms of performance."

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

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

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

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

"The solution integrates well with Power BI."

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

"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

"There may be some challenges in terms of connecting with Virtual Networks (VNETs) to Microsoft Azure Synapse Analytics."

"I don't have a direct relationship with the technical support when I have a problem. They aren't very good."

"There is a limit on the number of concurrent queries to around 125 for Azure Synapse."

"Comes with a pretty steep learning curve."

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

"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."

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

"The solution cannot store much data and might require purchasing additional storage. For example if you have 1 TB of data, processing it in the solution will cost ten times more than processing it in Databricks."

More Microsoft Azure Synapse Analytics cons

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

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

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

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

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

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

"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."

"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

"Microsoft's pricing is relatively high, and it varies according to the extent of our usage. The pricing is directly tied to our consumption. This decision is ultimately a business choice."

"The pricing is competitive, but only when you pay upfront. If you pay as you go, it's not as competitive. I'd give pricing a rating of seven out of ten."

"The solution could improve by having better costing information."

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

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

"All of the prices are available online."

"I understand that Synapse Analytics' pricing is lower than Informatica's."

"The price of this solution could be improved."

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."

"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."

"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."

"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."

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

"The solution's cost is reasonable."

More Oracle Autonomous Data Warehouse pricing and cost advice

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890,088 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

12%

Manufacturing Company

10%

Comms Service Provider

Government

Manufacturing Company

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	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...

What do you like most about Microsoft Azure Synapse Analytics?

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

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.

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.

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.

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

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

Snowflake vs Microsoft Azure Synapse Analytics

Comparisons

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

BigQuery vs Microsoft Azure Synapse Analytics

Compared 4% of the time

More Microsoft Azure Synapse Analytics Competitors

BigQuery vs Oracle Autonomous Data Warehouse

Compared 21% of the time

Snowflake vs Oracle Autonomous Data Warehouse

Compared 16% of the time

Databricks vs Oracle Autonomous Data Warehouse

Compared 11% 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

Microsoft Azure Synapse Analytics

Download Microsoft Azure Synapse Analytics product report

Microsoft Azure Synapse Analytics report

Oracle Autonomous Data Warehouse

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

Microsoft Azure Synapse Analytics vs. Oracle Autonomous Data Warehouse