Microsoft Azure Synapse Analytics vs Snowflake comparison

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Comparison Buyer's Guide
Executive Summary
Updated on Mar 24, 2022

We performed a comparison between Microsoft Azure Synapse Analytics and Snowflake based on our users’ reviews in four categories. After reading all of the collected data, you can find our conclusion below.

  • Ease of Deployment: Microsoft Azure Synapse Analytics reviewers had mixed reviews on the deployment, with many feeling it was complex. On the other hand, Snowflake reviewers felt it was an easy setup and deployment.
  • Features: Microsoft Azure Synapse Analytics users felt the software helped them control expenditures and was very scalable, but they had security concerns and felt the software wasn’t intuitive. Reviewers of Snowflake liked the stability and scalability of the solution and felt the software addressed challenges for traditional data warehouses, but said the UI needed improvement, especially when it came to extracting data.
  • Pricing: Users of Microsoft Azure Synapse Analytics gave mixed reviews on the pricing, with many feeling it was expensive. Users of Snowflake liked the efficient pricing model and felt it was high yet fair.
  • Service and Support: Both Microsoft Azure Synapse Analytics and Snowflake reviewers felt the support they received was helpful.

Comparison Results: Based on the parameters we compared, Snowflake had a better user rating regarding ease of deployment and pricing. Both softwares had the same rating when it came to service and support. In terms of features, Microsoft Azure Synapse Analytics users felt the software had security issues and didn’t feel it was very intuitive. In contrast, users of Snowflake felt the UI needed improvement.

To learn more, read our detailed Microsoft Azure Synapse Analytics vs. Snowflake Report (Updated: March 2024).
763,955 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
"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.""Microsoft provides both the platform and the data center, so you don't have to look for a cloud vendor. It saves you from having to deal with two vendors for the same task.""I have been working with Microsoft, and they have been very helpful.""I like how Microsoft Azure Synapse Analytics integrates with other Microsoft solutions.""Very interactive and provides flexibility.""The main advantage of using this solution is its ability to scale and handle very large amounts of data, in the petabyte range.""Overall deployment and integration is pretty fast.""Can capture all the transactional data throughout a company."

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"It is a highly scalable solution. There is no limit on storage or computing.""It is a very good platform. It can handle structured and semi-structured data, and it can be used for your data warehouse or data lake. It can load and deal with any data that you have. It can extract data from an on-premises database or a website and make it available in the cloud. It has very fast implementation and integration as compared to other solutions. There is no need for the DBA to manage or do the day-to-day DBA tasks, which is one of the greatest things about it.""The product is quite fast.""The syntax is advanced which reduces the time to write code.""It is a cloud solution with many useful features. It has the data science capability. It can transform data and prepare data for a data science project with scalability.""It's user-friendly. It's SQL-driven. The fact that business can also go to this application and query because they know SQL is the biggest factor.""The querying speed is fast.""Scaling is a big plus point of Snowflake."

More Snowflake 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.""Right now, we are really struggling with the performance. it's not as good as we had hoped.""Integration with other vendors has limitations and could be improved.""It would be beneficial to take the top vendors and identify some kind of straightforward action to work with them. Instead of having to employ a separate vendor tool to be able to move this, it would be nice to be able to go through Microsoft.""It's a complicated product.""I would like to see them provide the ingestion of images.""One area that could be improved is the schema management.""Scaling this solution up and down is not quick and easy. This could be improved. The pricing of this solution could also be improved."

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"In a future release we would like to have a link which would allow us to connect to an external database and create certain views in your own database. This is because it is becoming hard for us to compare the data between multiple sources.""Snowflake has to improve their spatial parts since it doesn't have much in terms of geo-spatial queries.""They need to improve its ETL functionality so that Snowflake becomes an ETL product. Snowpipe can do some pipelines and data ingestion, but as compare to Talend, these functionalities are limited. The ETL feature is not good enough. Therefore, Snowflake can only be used as a database. You can't use it as an ETL tool, which is a limitation. We have spoken to the vendor, and they said they are working on it, but I'm not sure when they will bring it to production.""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.""These aren't as crucial, but there are common errors sometimes where the database is down, or a table is nullified and a new table is added and you are not given access to that. With those errors, you don't have permissions.""Snowflake has support for stored procedures, but it is not that powerful.""There are three things that came to my notice. I am not very sure whether they have already done it. The first one is very specific to the virtual data warehouse. Snowflake might want to offer industry-specific models for the data warehouse. Snowflake is a very strong product with credit. For a typical retail industry, such as the pharma industry, if it can get into the functional space as well, it will be a big shot in their arm. The second thing is related to the migration from other data warehouses to Snowflake. They can make the migration a little bit more seamless and easy. It should be compatible, well-structured, and well-governed. Many enterprises have huge impetus and urgency to move to Snowflake from their existing data warehouse, so, naturally, this is an area that is critical. The third thing is related to the capability of dealing with relational and dimensional structures. It is not that friendly with relational structures. Snowflake is more friendly with the dimensional structure or the data masks, which is characteristic of a Kimball model. It is very difficult to be savvy and friendly with both structures because these structures are different and address different kinds of needs. One is manipulation-heavy, and the other one is read-heavy or analysis-heavy. One is for heavy or frequent changes and amendments, and the other one is for frequent reads. One is flat, and the other one is distributed. There are fundamental differences between these two structures. If I were to consider Snowflake as a silver bullet, it should be equally savvy on both ends, which I don't think is the case. Maybe the product has grown and scaled up from where it was.""The solution should offer an on-premises version also. We have some requirements where we would prefer to use it as a template."

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Pricing and Cost Advice
  • "The price of this solution could be improved."
  • "The pricing is okay. You can pay as you go."
  • "This solution starts at €1000.00 a month for just the basics and can go up to €300,000.00 per month for the fastest version."
  • "When we are not using this solution we can simply shut it down saving us costs, which is a nice advantage."
  • "The licensing fees for this solution are on a pay-per-use basis, and not very expensive."
  • "All of the prices are available online."
  • "Our license is very expensive"
  • "They are cost aggressive, and it integrates well with other Microsoft tools."
  • More Microsoft Azure Synapse Analytics 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: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… more »
    Top Answer:It is a highly stable solution and it's easy to use.
    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
    2nd
    Views
    19,142
    Comparisons
    9,225
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    37
    Average Words per Review
    462
    Rating
    8.1
    1st
    Views
    23,526
    Comparisons
    13,527
    Reviews
    40
    Average Words per Review
    455
    Rating
    8.4
    Comparisons
    Also Known As
    Azure Synapse Analytics, Microsoft Azure SQL Data Warehouse, Microsoft Azure SQL DW, Azure SQL Data Warehouse, MS Azure Synapse Analytics
    Snowflake Computing
    Learn More
    Overview

    Microsoft Azure Synapse Analytics is an end-to-end analytics solution that successfully combines analytical services to merge big data analytics and enterprise data warehouses into a single unified platform. The solution can run intelligent distributed queries among nodes, and provides the ability to query both relational and non-relational data.

    Microsoft Azure Synapse Analytics is built with these 4 components:

    1. Synapse SQL
    2. Spark
    3. Synapse Pipeline
    4. Studio

    Microsoft Azure Synapse Analytics Features

    Microsoft Azure Synapse Analytics has many valuable key features, including:

    • Cloud Data Service: WIth Microsoft Azure Synapse Analytics you can operate services (data analytics, machine learning, data warehousing, dashboarding, etc.) in a single workspace via the cloud.

    • Structured and unstructured data: Microsoft Azure Synapse Analytics supports both structured and unstructured data and allows you to manage relational and non-relational data - unlike data warehouses and lakes that tend to store them respectively.

    • Effective data storage: Microsoft Azure Synapse Analytics offers next-level data storage with high availability and different tiers.

    • Responsive data engine: Microsoft Azure Synapse Analytics uses Massive Parallel Processing (MPP) and is designed to handle large volumes of data and analytical workloads efficiently without any problems.

    • Several scripting languages: The solution provides language compatibility and supports different programming languages, such as Python, Java, Spark SQL, and Scala.

    • Query optimization: Microsoft Azure Synapse Analytics works well to facilitate limitless concurrency and performance optimization. It also simplifies workload management.

    Microsoft Azure Synapse Analytics Benefits

    Some of the benefits of using Microsoft Azure Synapse Analytics include:

    • Database templates: Microsoft Azure Synapse Analytics offers industry-specific database templates that make it easy to combine and shape data.

    • Better business insights: With Microsoft Azure Synapse Analytics you can expand discovery of insights from all your data and apply machine learning models to all your intelligent apps.

    • Reduce project development time: Microsoft Azure Synapse Analytics makes it possible to have a unified experience for developing end-to-end analytics, which reduces project development time significantly.

    • Eliminate data barriers: By using Microsoft Azure Synapse Analytics, you can perform analytics on operational and business apps data without data movement.

    • Advanced security: Microsoft Azure Synapse Analytics provides both advanced security and privacy features to ensure data protection.

    • Machine Learning: Microsoft Azure Synapse Analytics integrates Azure Machine Learning, Azure Cognitive Services, and Power BI.

    Reviews from Real Users

    Below are some reviews and helpful feedback written by Microsoft Azure Synapse Analytics users who are currently using the solution.

    PeerSpot user Jael S., who is an Information Architect at Systems Analysis & Design Engineering, comments on her experience using the product, saying that it is “Scalable, intuitive, facilitates compliance and keeps your data secure”. She also says "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."

    Michel T., CHTO at Timp-iT, mentions that "the features most valuable are the simplicity, how easy it is to create a dashboard from different information systems."

    A Senior Teradata Consultant at a tech services company says, "Microsoft provides both the platform and the data center, so you don't have to look for a cloud vendor. It saves you from having to deal with two vendors for the same task."


    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
      Toshiba, Carnival, LG Electronics, Jet.com, Adobe, 
      Accordant Media, Adobe, Kixeye Inc., Revana, SOASTA, White Ops
      Top Industries
      REVIEWERS
      Computer Software Company19%
      Financial Services Firm13%
      Manufacturing Company11%
      Comms Service Provider11%
      VISITORS READING REVIEWS
      Educational Organization30%
      Computer Software Company11%
      Financial Services Firm8%
      Manufacturing Company5%
      REVIEWERS
      Computer Software Company29%
      Financial Services Firm20%
      Healthcare Company6%
      Manufacturing Company6%
      VISITORS READING REVIEWS
      Educational Organization26%
      Financial Services Firm13%
      Computer Software Company10%
      Manufacturing Company6%
      Company Size
      REVIEWERS
      Small Business29%
      Midsize Enterprise18%
      Large Enterprise53%
      VISITORS READING REVIEWS
      Small Business15%
      Midsize Enterprise38%
      Large Enterprise47%
      REVIEWERS
      Small Business24%
      Midsize Enterprise20%
      Large Enterprise55%
      VISITORS READING REVIEWS
      Small Business15%
      Midsize Enterprise33%
      Large Enterprise52%
      Buyer's Guide
      Microsoft Azure Synapse Analytics vs. Snowflake
      March 2024
      Find out what your peers are saying about Microsoft Azure Synapse Analytics vs. Snowflake and other solutions. Updated: March 2024.
      763,955 professionals have used our research since 2012.

      Microsoft Azure Synapse Analytics is ranked 2nd in Cloud Data Warehouse with 38 reviews while Snowflake is ranked 1st in Cloud Data Warehouse with 40 reviews. Microsoft Azure Synapse Analytics is rated 8.0, while Snowflake is rated 8.4. The top reviewer of Microsoft Azure Synapse Analytics writes "Multifeatured, has better performance over other solutions, and lets users manage structured and unstructured information, but the platform needs to be more user-friendly". On the other hand, the top reviewer of Snowflake writes "Easy to set up with great cloning and time travel". Microsoft Azure Synapse Analytics is most compared with Azure Data Factory, SAP BW4HANA, Amazon Redshift, Oracle Autonomous Data Warehouse and Teradata, whereas Snowflake is most compared with BigQuery, Azure Data Factory, Teradata, Vertica and Amazon EMR. See our Microsoft Azure Synapse Analytics vs. Snowflake report.

      See our list of best Cloud Data Warehouse vendors and best 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.