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

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 June 2026, in the Cloud Data Warehouse category, the mindshare of Microsoft Azure Synapse Analytics is 5.8%, down from 6.2% compared to the previous year. The mindshare of Oracle Autonomous Data Warehouse is 4.7%, up from 4.7% 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	4.7%
Other	89.5%

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 pricing seems to be quite fair."

"It's feature-rich. It has a wide range of features."

"Our primary use case is for gathering data and analytics. We provide insights into vehicle data. We gather millions of records per second and we have various millions of vehicles running across."

"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 solution offers great flexibility and the resource availability is quite good."

"The platform has multiple valuable use cases. They include performance, compatibility, flexibility, and cost."

"The solution is like a marketplace in that it's easy to consume; it's scalable, you can scale up and scale down, and the standard things that you see from any cloud perspective make it very attractive."

"The most valuable feature is the scalability, because it scales out so you can build a large database and not have to think about whether it performs or about connecting to the servers to become larger."

More Microsoft Azure Synapse Analytics pros

"Self-patching and runs machine-learning across its logs all the time"

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

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

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

"It is a stable and scalable solution."

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

"The product is easy to use."

"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."

More Oracle Autonomous Data Warehouse pros

Cons

"Microsoft Azure Synapse Analytics can improve by adding more flexibility to the reports. Having more visible structures based on the area, region and country would be beneficial."

"Synapse Analytics is generally stable, but its performance can be slow when performing very large datasets."

"In the last six months, there have been a couple of incidents. We have experienced some outages."

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

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

"Microsoft Azure Synapse Analytics could improve its compatibility with Visual Studio. One of the challenges for people moving from an on-premise to a cloud solution, such as Microsoft Azure Synapse Analytics, is that you're constantly working in a browser. There are people that have been working for decades on desktop applications. For them to start working in a browser, it's quite a change. Allowing people to work and do their work inside Visual Studio than in the browser, would be a large advantage."

"If Microsoft Azure Synapse Analytics could run on a laptop as a Docker image, it would allow for work without needing an online connection."

"The performance needs to improve in future releases."

More Microsoft Azure Synapse Analytics cons

"Ease of connectivity could be improved."

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

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

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

"Optimization should be better."

"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."

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

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

More Oracle Autonomous Data Warehouse cons

Pricing and Cost Advice

"It's very difficult to price unless you know exactly how the customer is using it."

"Price is dependent of the use case of the customer. Customers are not likely to only use this as an individual platform/database, they are likely to bundle it with the Azure stack."

"Pay for what you use"

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

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

"The costs are billed such that we pay for what we use, which is a good thing."

"The cost of the solution depends on the type of license we choose, such as pay-as-you-go, one-year reserve, or three-year reserve."

"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

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

"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."

"The cost is perfect with Oracle Universal credit."

"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."

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

"The solution's cost is reasonable."

"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."

More Oracle Autonomous Data Warehouse pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

12%

Manufacturing Company

Construction Company

Comms Service Provider

Manufacturing Company

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 6% 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 18% 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

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