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Oracle Autonomous Data Warehouse vs Snowflake Analytics comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 18, 2024

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

Oracle Autonomous Data Ware...
Ranking in Cloud Data Warehouse
12th
Average Rating
8.4
Reviews Sentiment
7.2
Number of Reviews
19
Ranking in other categories
No ranking in other categories
Snowflake Analytics
Ranking in Cloud Data Warehouse
10th
Average Rating
8.4
Reviews Sentiment
7.1
Number of Reviews
42
Ranking in other categories
Web Analytics (2nd)
 

Mindshare comparison

As of October 2025, in the Cloud Data Warehouse category, the mindshare of Oracle Autonomous Data Warehouse is 5.2%, up from 4.3% compared to the previous year. The mindshare of Snowflake Analytics is 1.1%, up from 0.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Warehouse Market Share Distribution
ProductMarket Share (%)
Snowflake Analytics1.1%
Oracle Autonomous Data Warehouse5.2%
Other93.7%
Cloud Data Warehouse
 

Featured Reviews

Kwajah Mohiuddin - PeerSpot reviewer
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…
Garima Goel - PeerSpot reviewer
Have created secure cloud-based data lakes and improved real-time data processing using integrated AI features
There are many capabilities which Snowflake Analytics offers that I find valuable, such as the storage and compute engine that allows working with any cloud system such as AWS or Azure, alongside its efficiencies in storage computation and cost-effectiveness, which saves money compared to on-premise systems. We also have features such as pre-cached results, Time Travel, and fail-safe, which are very useful for restoring data if deleted accidentally, and the streams and data pipes that facilitate real-time ingestion are great features as well. Snowflake Analytics offers multiple new connectors, allowing me to connect it with Kafka, and with Snowpark, I can work with any programming language such as Python, Java, or Scala for data processing and analysis. The data sharing feature offered by Snowflake Analytics is good because it allows sharing specific sets of data to end customers or users from different Snowflake Analytics accounts without exposing the entire dataset for data security reasons. Snowflake Analytics' support for machine learning models and real-time insights has enhanced significantly. Originally, it wasn't strong in AI/ML, but now it has multiple models and forecasting capabilities, providing good competition to tools such as Databricks and Spark. In BI, I have worked majorly with Microsoft Power BI, and the integration with Snowflake Analytics is very easy. The way we integrate Snowflake Analytics with other on-premise systems just requires the warehouse details, username, passwords, and the account name, along with multiple options such as client ID and credentials for logging in and creating a session. The end-to-end encryption provided by Snowflake Analytics is very important because, in my previous firm, working in finance and investment management, data encryption is necessary due to the sensitive nature of customer data and the involvement of people's money. It's crucial to have encryption in transit and at rest, along with data masking features which Snowflake Analytics offers.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"The analytics have been very good. We've found them to be quite useful."
"I really like the auto-tuning, auto-scaling, and the automatic load balancing and query tuning in the system."
"It is a stable and scalable solution."
"The solution is used for analytics and it works for our data security needs."
"The performance and scalability are awesome."
"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."
"It is an extremely scalable solution since you can dynamically change the resources as some other cloud solutions."
"It is quite a convenient tool."
"It helps with business intelligence by providing analytics that can be reported."
"The computational power of Snowflake is very good."
"Snowflake Analytics is pretty easy to use with the connectors for integration with the tools and systems in my company."
"It's a scalable solution because you can analyze a huge amount of data in the solution."
"Scalability-wise, I rate the solution a ten out of ten."
"What we found most valuable in Snowflake Analytics are its attributes that are very convenient for business use such as data sharing, cloning, time travel, and fail-safe. It's a good product all in all."
"Very good flexibility and it offers computation completely decoupled from the storage."
 

Cons

"The setup is complex."
"The installation process is complex. Oracle can make the installation process better."
"Sometimes the solution works differently between the cloud and on-premises. It needs to be more consistent and predictable."
"A lot of the tools that were previously there have now been taken away."
"I would like to see an on-premise solution in the future."
"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."
"The initial setup was pretty complex. It was not easy."
"Ease of connectivity could be improved."
"Machine learning in Snowflake isn't as advanced as in other products. I haven't heard of any successful industry-wide use cases of machine learning implemented in Snowflake. It might take a couple of years to reach the same level as Databricks."
"Snowflake should include a WHERE clause for building data pipelines."
"Snowflake Analytics can improve the integration with machine learning tools and AI and it will make the solution more usable."
"Snowflake could improve in the areas of advanced machine learning AML and generative AI."
"Moving data from legacy systems to Snowflake is not that easy. There are some cases where processors are not actually compatible with Snowflake."
"The platform could work easier for AI implementation compared to one of its competitors."
"We were experiencing errors while running reports and making connections."
"The UI must be improved."
 

Pricing and Cost Advice

"You pay as you go, and you don't pay for services that you don't use."
"The solution is 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."
"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."
"We pay approximately $70,000 per month. The cost includes maintenance and support."
"The cost is perfect with Oracle Universal credit."
"The solution's cost is reasonable."
"The price depends on the configuration we choose."
"I have been using free trial version."
"The tool is quite expensive."
"Snowflake charges per query, which amounts to a very minor cost, such as $0.015 per query."
"When using Snowflake, you pay based on your usage. They calculate how much CPU has been used. If you use excess warehouse storage, you are charged one credit per hour. If you are in Asia, you are charged $3 per credit. If you have 10 users running parallel with the same excess, you will be charged $30."
"The solution's pricing is affordable."
"On a scale of one to ten, where one is a low price, and ten is a high price, I rate the pricing a seven. The solution's pricing is high."
"Snowflake Analytics is a little more costly than Azure."
"It's not costly if you configure it properly to ensure optimal performance. People don't configure it properly, which is why costs go up."
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Top Industries

By visitors reading reviews
Computer Software Company
10%
Manufacturing Company
8%
University
7%
Insurance Company
7%
Computer Software Company
16%
Retailer
9%
Financial Services Firm
9%
Government
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business6
Midsize Enterprise1
Large Enterprise11
By reviewers
Company SizeCount
Small Business10
Midsize Enterprise12
Large Enterprise21
 

Questions from the Community

What do you like most about Oracle Autonomous Data Warehouse?
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...
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 experience regarding pricing and costs for Snowflake Analytics?
Snowflake Analytics is quite economical. It does not appear to incur significant extra expenses beyond the solution's initial cost. However, a complete pricing analysis is still in progress.
What needs improvement with Snowflake Analytics?
There are some minor issues encountered with Snowflake Analytics, such as problems when working with identity or row number generating different results or issues with referential integrity, which ...
 

Overview

 

Sample Customers

Hertz, TaylorMade Golf, Outront Media, Kingold, FSmart, Drop-Tank
Lionsgate, Adobe, Sony, Capital One, Akamai, Deliveroo, Snagajob, Logitech, University of Notre Dame, Runkeeper
Find out what your peers are saying about Oracle Autonomous Data Warehouse vs. Snowflake Analytics and other solutions. Updated: September 2025.
869,566 professionals have used our research since 2012.