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

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

"They are available on the Cloud, and the platform is very intuitive."

"The solution is scalable."

"The most advantageous aspect of Microsoft Azure Synapse Analytics is its simplified data transformation process compared to traditional databases. This makes data cleansing and transformation more manageable and straightforward, which we appreciate. It is much easier to build as well."

"We find the serverless tool to be the most valuable feature ."

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

"It is a highly stable solution and it's easy to use."

"The most valuable feature is the level of processing power, and being able to complete tasks in parallel."

"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."

More Microsoft Azure Synapse Analytics pros

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

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

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

"The product is easy to use."

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

"It is a stable and scalable solution."

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

"Amazing performance, it is a revolution."

More Oracle Autonomous Data Warehouse pros

Cons

"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."

"I am very sure that there are areas in need of improvement, but I can't recall what they are off the top of my head."

"It would be of interest to improve things like the web service integration and availability in terms of being easy to create internal web services in the database."

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

"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."

"The only issue that we have run into with the solutions performance is with regards to concurrency."

"As far as improvements to the product, I think the Data Factory integration should be enhanced to be properly implemented because right now it is still lagging behind other vendors like Informatica."

"Its stability is an issue. They have been releasing a version every six months to one year, which means that there are many versions available, and clients are not up to speed on the latest one that they're offering. From a stability point of view, they could do better. They're still upgrading their Synapse Analytics workspace, and it is not that stable. Its scalability can also be better."

More Microsoft Azure Synapse Analytics cons

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

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

"Ease of connectivity could be improved."

"I would like to see Application Express and Oracle R Enterprise fully supported, and I would like to see Oracle Data Mining supported as a front end."

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

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

"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."

"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."

More Oracle Autonomous Data Warehouse cons

Pricing and Cost Advice

"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."

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

"The solution is subscription-based. You can also pay to use the product as you go."

"This is an expensive solution."

"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 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."

"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 quite reasonable in comparison to other products."

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."

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

"ROI is high."

"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."

"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 is expensive."

"The price depends on the configuration we choose."

"The cost is perfect with Oracle Universal credit."

More Oracle Autonomous Data Warehouse pricing and cost advice

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903,182 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

12%

Manufacturing Company

Construction Company

Comms Service Provider

Manufacturing Company

10%

Financial Services Firm

Media Company

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...

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 needs improvement with Microsoft Azure Synapse Analytics?

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

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 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

BigQuery vs Microsoft Azure Synapse Analytics

Compared 5% of the time

SAP BW4HANA vs Microsoft Azure Synapse Analytics

Compared 5% of the time

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BigQuery vs Oracle Autonomous Data Warehouse

Compared 17% of the time

Snowflake vs Oracle Autonomous Data Warehouse

Compared 17% 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 5% of the time

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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