Microsoft Azure Synapse Analytics vs Snowflake comparison

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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: November 2022).
656,862 professionals have used our research since 2012.
Q&A Highlights
Question: Which is better - Azure Synapse Analytics or Snowflake?
Answer: If you are dealing with semi-structured data like json Snowflake has great support in handling and querying json data. it is also good to use as data lake and can act as one stop solution for a data lake and cloud data warehouse. query performance and low maintainability is also what makes snowflake a great choice.
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 useability, the user interface, is very user-friendly.""Data can be stored any way you want in the data warehouse.""The whole solution is interesting for us.""The most valuable feature of Microsoft Azure Synapse Analytics is the pipeline that is the ETL tool. It's very well designed and is overall very good. We usually don't use the ETL tool in Databricks, but we use the ETL tool in this solution.""The most valuable feature of Microsoft Azure Synapse Analytics is its integration with the new legacy systems. Whatever application we want to integrate, we receive the reports based on the objects. The solution is easy to purchase from the cloud.""The solution operates like a typical SQL Server environment so there is no alienation in terms of technical knowledge.""They are very reliable and cost-effective.""The most valuable features of Microsoft Azure Synapse Analytics are the interface and the agility of the on-cloud platform."

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"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.""The overall ecosystem was easy to manage. Given that we weren't a very highly technical group, it was preferable to other things we looked at because it could do all of the cloud tunings. It can tune your data warehouse to an appropriate size for controlled billing, resume and sleep functions, and all such things. It was much more simple than doing native Azure or AWS development. It was stable, and their support was also perfect. It was also very easy to deploy. It was one of those rare times where they did exactly what they said they could do.""The most valuable features are sharing data, Time Travel, Zero Copy Cloning, performance, and speed.""All the people who are working with Snowflake are extremely happy with it because it is designed from a data-warehousing point of view, not the other way around. You have a database and then you tweak it and then it becomes a data warehouse.""The solution is stable.""The most valuable feature has been the Snowflake data sharing and dynamic data masking.""The Time Travel feature is helpful for accessing historical data and the ability to clone external tables is useful.""Its performance is most valuable. As compared to SQL Server, we are able to see a significant improvement in performance with Snowflake."

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Cons
"Microsoft Azure Synapse Analytics could improve the section in the solution where you can implement the Python Spark pipelines, it's not the same as in Databricks which would be better.""Synapse Analytics' performance slows down if you don't get your distribution right because it gets queued and goes into a single node.""Right now, we are really struggling with the performance. it's not as good as we had hoped.""The macro functions, though useful, are not totally user-friendly. Some people have difficulties in learning them.""The only issue that we have run into with the solutions performance is with regards to concurrency.""Synapse Analytics is generally stable, but its performance can be slow when performing very large datasets.""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.""Indicating what areas need improvement in this solution is a difficult question because the organizations that I am working for are really new in this area. However, an even better more simple interface, or perhaps an extension of a connector app store solution, would be helpful."

More Microsoft Azure Synapse Analytics Cons →

"It would be better if they had a data profile tool that tells me where the gaps are in my time series data.""Snowflake has to build more capabilities because they have only built very few adapters, but they're growing and they're building. They should provide provisions to collect ETL pipeline capabilities, reduce developer work, and make more rapid application development, rather than some customizations. There are very few options, but they are building. I hope they will build ETL rapid application development provisions with more variety.""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.""The solution could use a little bit more UI.""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 scheduling system can definitely be better because we had to use external airflow for that. There should be orchestration for the scheduling system. Snowflake currently does not support machine learning, so it is just storage. They also need some alternatives for SQL Query. There should also be support for Spark in different languages such as Python.""This solution could be improved by offering machine learning apps.""There is a need for improvements in the documentation, this would allow more people to switch over to this solution."

More Snowflake Cons →

Pricing and Cost Advice
  • "This is a cost-effective product."
  • "Because it's cloud the cost is a different convention and the licensing costs are not the same."
  • "It's very difficult to price unless you know exactly how the customer is using it."
  • "We normally pay between $300 and $500 per month, which is quite expensive for how much we actually use it, performance- and usage-wise. They have a cheap version and an expensive version, and our usage usually falls in the middle ground, which makes it not as cost-effective as it could be."
  • "The solution is subscription-based. You can also pay to use the product as you go."
  • "It requires a less expensive version because currently, not every customer is able to buy it. If it could have a smaller setup that doesn't require so many resources, it would be helpful, and we would be able to use it in more cases. We are a small country, and most of our customers are quite small businesses."
  • "It goes by the usage, and there are some limits. Synapse goes by particular pricing, and it is expensive. Both Azure Synapse Analytics and Snowflake are pretty expensive. They don't have standard pricing. They deal with each customer differently."
  • "My company pays for the license and I am not sure about the price."
  • More Microsoft Azure Synapse Analytics Pricing and Cost Advice →

  • "The price of Snowflake is quite reasonable."
  • "Its price should be improved. It should be cheaper than Microsoft."
  • "It is per credit. It has a use-it-as-you-go model. We bought a chunk of 20,000 credits, and they were lasting us for at least a year. We didn't have the scale of data like a much larger company to consume more credits. For us, it was very inexpensive. Their strategy is just to leverage what you've got and put Snowflake in the middle. It doesn't make it expensive because most of the organizations already have reporting tools. Now, if you were starting from scratch, it might be cheaper to go a different way."
  • "We used Snowflake to see if it is cheaper than using BigQuery. It was just to maintain the cost or the KPI regarding the cost of connectivity by users. Snowflake wasn't cheaper than BigQuery, and its affordability was the main issue."
  • "Currently, we have a trial account, so we don't need a license. After our project starts, we would need a permanent license."
  • "Snowflake goes by credits. For a financial institution where you have 5,000 employees, monthly costs may run up to maybe $5,000 to $6,000. This is actually based on the usage. It is mostly the compute cost. Your computing cost is the variable that is actually based on your usage. It is pay-per-use. In a pay-per-use case, you won't be spending more than $6,000 to $7,000 a month. It is not more than that for a small or medium enterprise, and it may come down to $100K per year. Storage is very standard, which is $23 a terabyte. It is not much for any enterprise. If you have even 20 terabytes, you are not spending more than $400 per month, which may turn out to be $2,000 to $3,000 per annum."
  • "It is on a monthly basis. It is based on your usage. There are no additional costs from the point of the licensing fee. We do give some kind of evaluation to the customers about how much it is going to be. You can decide in Snowflake the virtual machine that you are using for customers. There are several kinds of virtual machines that you can use. It is similar to the clothing sizes: small to extra large. If you need more power in the coming month, you can decide in advance and take a more powerful machine. You can just select it from the platform. You can also decide which machine you want to take for extracting data."
  • "They give a different price for every single company. I don't know if I negotiated that well, but we got the enterprise tier for $3 a credit, and the other two were a dollar-ninety a credit. I suspect we don't have almost zero compute usage, but I know that our annual contract packages are below all of their minimums."
  • 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:Traditional ETL would usually use a dedicated database (or even database server) where you'll load & transform your raw data before ingesting it into the final destination. This would allow checking… more »
    Top Answer:The most valuable feature of Microsoft Azure Synapse Analytics is the pipeline that is the ETL tool. It's very well designed and is overall very good. We usually don't use the ETL tool in Databricks… more »
    Top Answer:A user-friendly and reliable solution.
    Top Answer:It's important to understand the licensing model because if you're paying for the software, you're not necessarily aware of the use. It's important to monitor how you're using the resources otherwise… more »
    Top Answer:I'd like to see the data science functionality improved to a degree that would enable data scientists to work together with the data engineering team. The solution is focused on SQL and some kind of… more »
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    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 fully managed SaaS (software as a service) that provides a single platform for data warehousing, data lakes, data engineering, data science, data application development, and secure sharing and consumption of real-time / shared data.

    Its platform is made up of three components:

    1. Cloud services: As part of its cloud services, Snowflake uses ANSI SQL, which empowers users to optimize their data and manage their infrastructure, while Snowflake handles the security and encryption of stored data.
    1. Query processing: With Snowflake, workload concurrency is never a problem because its compute layer is made up of virtual cloud data warehouses that let you analyze data through requests. Each of the warehouses do not compete for computing resources nor do they affect the performance of each other.
    1. Database storage: Snowflake manages all parts of the data storage process automatically, including file size, compression, organization, structure, and metadata, as well as statistics.

    Snowflake Features

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

    • Scalability: Snowflake architecture provides nearly unlimited scalability and high speed because it uses a single elastic performance engine. The solution also supports an unlimited amount of concurrent users and workloads, from interactive to batch.
    • Automation: Snowflake makes automation easy and enables enterprises to automate data management, security, governance, availability, and data resiliency.
    • Seamless cross-cloud and cross-region connections: 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.
    • Third-party data integrations: 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.

    Snowflake Benefits

    There are many benefits to implementing Snowflake. Some of the biggest advantages the solution offers include:

    • Helps optimize costs
    • Reduces downtime
    • Improves operational efficiency
    • Built for high reliability and availability
    • Automates data replication for fast recovery

    Reviews from Real Users

    Below are some reviews and helpful feedback written by PeerSpot 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 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."

    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."

    Offer
    Learn more about Microsoft Azure Synapse Analytics
    Learn more about Snowflake
    Sample Customers
    Toshiba, Carnival, LG Electronics, Jet.com, Adobe, 
    Accordant Media, Adobe, Kixeye Inc., Revana, SOASTA, White Ops
    Top Industries
    REVIEWERS
    Computer Software Company26%
    Comms Service Provider12%
    Financial Services Firm12%
    Manufacturing Company9%
    VISITORS READING REVIEWS
    Computer Software Company20%
    Comms Service Provider10%
    Financial Services Firm9%
    Manufacturing Company6%
    REVIEWERS
    Computer Software Company37%
    Financial Services Firm16%
    Manufacturing Company8%
    Comms Service Provider5%
    VISITORS READING REVIEWS
    Computer Software Company18%
    Financial Services Firm13%
    Comms Service Provider8%
    Insurance Company6%
    Company Size
    REVIEWERS
    Small Business29%
    Midsize Enterprise22%
    Large Enterprise49%
    VISITORS READING REVIEWS
    Small Business18%
    Midsize Enterprise14%
    Large Enterprise68%
    REVIEWERS
    Small Business23%
    Midsize Enterprise21%
    Large Enterprise56%
    VISITORS READING REVIEWS
    Small Business18%
    Midsize Enterprise13%
    Large Enterprise69%
    Buyer's Guide
    Microsoft Azure Synapse Analytics vs. Snowflake
    November 2022
    Find out what your peers are saying about Microsoft Azure Synapse Analytics vs. Snowflake and other solutions. Updated: November 2022.
    656,862 professionals have used our research since 2012.

    Microsoft Azure Synapse Analytics is ranked 3rd in Cloud Data Warehouse with 48 reviews while Snowflake is ranked 1st in Cloud Data Warehouse with 49 reviews. Microsoft Azure Synapse Analytics is rated 7.8, 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 "Good usability, good data sharing and elastic compute features, and requires less DBA involvement". Microsoft Azure Synapse Analytics is most compared with Amazon Redshift, Azure Data Factory, SAP BW4HANA, Apache Hadoop and AWS Lake Formation, whereas Snowflake is most compared with Teradata, Vertica, Azure Data Factory, Amazon Redshift and AWS Lake Formation. See our Microsoft Azure Synapse Analytics 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.