Oracle Autonomous Data Warehouse vs Snowflake comparison

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3,362 views|2,210 comparisons
100% willing to recommend
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21,234 views|11,994 comparisons
96% willing to recommend
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Executive Summary

We performed a comparison between Oracle Autonomous Data Warehouse and Snowflake based on real PeerSpot user reviews.

Find out in this report how the two Cloud Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
To learn more, read our detailed Oracle Autonomous Data Warehouse vs. Snowflake Report (Updated: March 2024).
769,976 professionals have used our research since 2012.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"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.""The performance and scalability are awesome.""It is a very stable tool...It is an extremely scalable tool.""Self-patching and runs machine-learning across its logs all the time""The analytics have been very good. We've found them to be quite useful.""It is an extremely scalable solution since you can dynamically change the resources as some other cloud solutions.""The solution integrates well with Power BI.""It is a stable and scalable solution."

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"Its performance is most valuable. As compared to SQL Server, we are able to see a significant improvement in performance with Snowflake.""The most valuable feature is the clone copy.""The solution is stable.""For us, the virtual warehousing is likely the most valuable aspect.""The ETL and data ingestion capabilities are better in this solution as compared to SQL Server. SQL Server doesn't do much data ingestion, but Snowflake can do it quite conveniently.""Data sharing is a good feature. It is a majorly used feature. The elastic compute is another big feature. Separating compute and storage gives you flexibility. It doesn't require much DBA involvement because it doesn't need any performance tuning. We are not really doing any performance tuning, and the entire burden of performance tuning and SQL tuning is on Snowflake. Its usability is very good. I don't need to ramp up any user, and its onboarding is easier. You just onboard the user, and you are done with it. There are simple SQL and UI, and people are able to use this solution easily. Ease of use is a big thing in Snowflake.""The cloning functionality has been the most valuable. I have been able to completely copy databases. The data sharing concept is also useful. As compared to, for example, SAP, Snowflake is a lot more open, and it allows a lot more connectivity for other providers than an SAP ecosystem.""Everything is automatic, and I don't have to do any maintenance."

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Cons
"An improvement for us would be the inclusion of support for an internal IP, so we could use it directly with the VCN in Oracle Cloud.""The solution could be improved by allowing for migration tools from other cloud services, including migration from Amazon Redshift, RDS, and Aurora.""I would like to see an on-premise solution in the future.""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.""It is very important the integration with other platforms be made to be as easy as it is with an on-premises deployment.""The solution lacks visibility options.""The initial setup was pretty complex. It was not easy."

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"Their strategy is just to leverage what you've got and put Snowflake in the middle. It does work well with other tools. You have to buy a separate reporting tool and a separate data loading tool, whereas, in some platforms, these tools are baked in. In the long-term, they'll need to add more direct partnerships to the ecosystem so that it's not like adding on tools around Snowflake to make it work. They can also consider including Snowflake native reporting tools versus partnering with other reporting tools. It would kind of change where they sit in the market.""They do have a native connector to connect with integration tools for loading data, but it would be much better to have the functionality built-in.""Pricing is an issue for many customers.""There are a lot of features that they need to come up with. A lot of functions are missing in Snowflake, so we have to find a workaround for those. For example, OUTER APPLY is a basic function in SQL Server, but it is not there in Snowflake. So, you have to write complex code for it.""There are some challenges with loading unstructured data and integrating some message queues or brokers. In one project, we had a problem connecting to one of the message queues and we had to take a different route altogether on Microsoft Azure.""Its transaction application needs improvement.""Snowflake could improve migration. It should be made easier. It would be beneficial if it could offer some OLTP features. One of our customers was using Oracle for both data warehousing and OLTP workloads, and they were able to migrate their data warehousing workloads to Snowflake without major issues. However, for some of their OLTP requirements, such as needing a response time of fewer than 10 milliseconds for certain queries, Snowflake is currently unable to provide that.""We would like to have an on-premises deployment option that has the same features, including scalability."

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Pricing and Cost Advice
  • "The cost is perfect with Oracle Universal credit."
  • "ROI is high."
  • "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 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."
  • "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."
  • "The price depends on the configuration we choose."
  • More Oracle Autonomous Data Warehouse Pricing and Cost Advice →

  • "Pricing can be confusing for customers."
  • "The whole licensing system is based on credit points. You can also make a license agreement with the company so that you buy credit points and then you use them. What you do not use in one year can be carried over to the next year."
  • "You pay based on the data that you are storing in the data warehouse and there are no maintenance costs."
  • "It is not cheap."
  • "The pricing for Snowflake is competitive."
  • "On average, with the number of queries that we run, we pay approximately $200 USD per month."
  • "Pricing is approximately $US 50 per DB. Terabyte is around $US 50 per month."
  • "The price of Snowflake is very reasonable."
  • More Snowflake Pricing and Cost Advice →

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    Questions from the Community
    Top Answer: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… more »
    Top Answer:Cost-wise, it's a solid seven out of ten. A bit costly, but it is a good tool.
    Top Answer: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… more »
    Top Answer:The best thing about Snowflake is its flexibility in changing warehouse sizes or computational power.
    Top Answer:The real-time streaming feature is limited with Snowflake and could be improved. Currently, Snowflake doesn't support unstructured data. With Snowflake, you need to be very particular about the type… more »
    Ranking
    10th
    Views
    3,362
    Comparisons
    2,210
    Reviews
    7
    Average Words per Review
    556
    Rating
    8.1
    1st
    Views
    21,234
    Comparisons
    11,994
    Reviews
    36
    Average Words per Review
    464
    Rating
    8.3
    Comparisons
    Also Known As
    Snowflake Computing
    Learn More
    Overview

    Oracle Autonomous Data Warehouse is the world’s first and only autonomous database optimized for analytic workloads, including data marts, data warehouses, data lakes, and data lakehouses. With Autonomous Data Warehouse, data scientists, business analysts, and nonexperts can rapidly, easily, and cost-effectively discover business insights using data of any size and type. Built for the cloud and optimized using Oracle Exadata, Autonomous Data Warehouse benefits from faster performance and, according to an IDC report (PDF), lowers operational costs by an average of 63%.


    Autonomous Database provides the foundation for a data lakehouse—a modern, open architecture that enables you to store, analyze, and understand all your data. The data lakehouse combines the power and richness of data warehouses with the breadth, flexibility, and low cost of popular open source data lake technologies. Access your data lakehouse through Autonomous Database using the world's most powerful and open SQL processing engine.

    Snowflake is a cloud-based data warehousing solution for storing and processing data, generating reports and dashboards, and as a BI reporting source. It is used for optimizing costs and using financial data, as well as for migrating data from on-premises to the cloud. The solution is often used as a centralized data warehouse, combining data from multiple sources.

    Snowflake has helped organizations improve query performance, store and process JSON and XML, consolidate multiple databases into one unified table, power company-wide dashboards, increase productivity, reduce processing time, and have easy maintenance with good technical support.

    Its platform is made up of three components:

    1. Cloud services - Snowflake uses ANSI SQL to empower users to optimize their data and manage their infrastructure, while Snowflake handles the security and encryption of stored data.
    2. Query processing - Snowflake's compute layer is made up of virtual cloud data warehouses that let you analyze data through requests. Each of the warehouses does not compete for computing resources, nor do they affect the performance of each other.
    3. Database storage - Snowflake automatically manages all parts of the data storage process, including file size, compression, organization, structure, metadata, and statistics.

    Snowflake has many valuable vital features. Some of the most useful ones include:

    • Snowflake architecture provides nearly unlimited scalability and high speed because it uses a single elastic performance engine. The solution also supports unlimited concurrent users and workloads, from interactive to batch.
    • Snowflake makes automation easy and enables enterprises to automate data management, security, governance, availability, and data resiliency.
    • With seamless cross-cloud and cross-region connections, Snowflake eliminates ETL and data silos. Anyone who needs access to shared secure data can get a single copy via the data cloud. In addition, Snowflake makes remote collaboration and decision-making fast and easy via a single shared data source.
    • Snowflake’s Data Marketplace offers third-party data, which allows you to connect with Snowflake customers to extend workflows with data services and third-party applications.

    There are many benefits to implementing Snowflake. It helps optimize costs, reduce downtime, improve operational efficiency, and automate data replication for fast recovery, and it is built for high reliability and availability.

      Below are quotes from interviews we conducted with users currently using the Snowflake solution:

      Sreenivasan R., Director of Data Architecture and Engineering at Decision Minds, says, "Data sharing is a good feature. It is a majorly used feature. The elastic computing is another big feature. Separating computing and storage gives you flexibility. It doesn't require much DBA involvement because it doesn't need any performance tuning. We are not doing any performance tuning, and the entire burden of performance and SQL tuning is on Snowflake. Its usability is very good. I don't need to ramp up any user, and its onboarding is easier. You just onboard the user, and you are done with it. There are simple SQL and UI, and people are able to use this solution easily. Ease of use is a big thing in Snowflake."

      A director of business operations at a logistics company mentions, "It requires no maintenance on our part. They handle all that. The speed is phenomenal. The pricing isn't really anything more than what you would be paying for a SQL server license or another tool to execute the same thing. We have zero maintenance on our side to do anything and the speed at which it performs queries and loads the data is amazing. It handles unstructured data extremely well, too. So, if the data is in a JSON array or an XML, it handles that super well."

      A Solution Architect at a wholesaler/distributor comments, "The ability to share the data and the ability to scale up and down easily are the most valuable features. The concept of data sharing and data plumbing made it very easy to provide and share data. The ability to refresh your Dev or QA just by doing a clone is also valuable. It has the dynamic scale up and scale down feature. Development and deployment are much easier as compared to other platforms where you have to go through a lot of stuff. With a tool like DBT, you can do modeling and transformation within a single tool and deploy to Snowflake. It provides continuous deployment and continuous integration abilities. There is a separation of storage and compute, so you only get charged for your usage. You only pay for what you use. When we share the data downstream with business partners, we can specifically create compute for them, and we can charge back the business."

      Sample Customers
      Hertz, TaylorMade Golf, Outront Media, Kingold, FSmart, Drop-Tank
      Accordant Media, Adobe, Kixeye Inc., Revana, SOASTA, White Ops
      Top Industries
      REVIEWERS
      Computer Software Company27%
      Manufacturing Company18%
      Financial Services Firm18%
      Individual & Family Service9%
      VISITORS READING REVIEWS
      Educational Organization43%
      Financial Services Firm9%
      Computer Software Company8%
      Manufacturing Company4%
      REVIEWERS
      Computer Software Company29%
      Financial Services Firm20%
      Healthcare Company6%
      Manufacturing Company6%
      VISITORS READING REVIEWS
      Educational Organization27%
      Financial Services Firm13%
      Computer Software Company10%
      Manufacturing Company6%
      Company Size
      REVIEWERS
      Small Business38%
      Midsize Enterprise6%
      Large Enterprise56%
      VISITORS READING REVIEWS
      Small Business13%
      Midsize Enterprise48%
      Large Enterprise39%
      REVIEWERS
      Small Business24%
      Midsize Enterprise20%
      Large Enterprise55%
      VISITORS READING REVIEWS
      Small Business15%
      Midsize Enterprise34%
      Large Enterprise51%
      Buyer's Guide
      Oracle Autonomous Data Warehouse vs. Snowflake
      March 2024
      Find out what your peers are saying about Oracle Autonomous Data Warehouse vs. Snowflake and other solutions. Updated: March 2024.
      769,976 professionals have used our research since 2012.

      Oracle Autonomous Data Warehouse is ranked 10th in Cloud Data Warehouse with 16 reviews while Snowflake is ranked 1st in Cloud Data Warehouse with 92 reviews. Oracle Autonomous Data Warehouse is rated 8.6, while Snowflake is rated 8.4. The top reviewer of Oracle Autonomous Data Warehouse writes "A tool for data warehousing that offers scalability, stability, and ease of setup". On the other hand, the top reviewer of Snowflake writes "Good usability, good data sharing and elastic compute features, and requires less DBA involvement". Oracle Autonomous Data Warehouse is most compared with Oracle Exadata, Microsoft Azure Synapse Analytics, BigQuery, Amazon Redshift and Teradata, whereas Snowflake is most compared with BigQuery, Azure Data Factory, Teradata, Vertica and Amazon EMR. See our Oracle Autonomous Data Warehouse vs. Snowflake 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.