Snowflake and Microsoft Azure Synapse Analytics compete in the cloud data warehousing and analytics category. Snowflake seems to have the upper hand due to its emphasis on scalability and ease of use, which is consistently highlighted in user feedback.
Features: Snowflake offers seamless data scaling, managed service operations, and micro-partitioning, making it more user-friendly. Azure Synapse, on the other hand, provides robust data processing and strong integration within Microsoft's ecosystem, making it ideal for environments already using Microsoft tools.
Room for Improvement: Snowflake users look for better geo-spatial queries, enhanced stored procedure support, and a more transparent pricing model. Azure Synapse users point to a complex interface, cost concerns, and a lack of real-time integration, suggesting improvements in IoT support and advanced analytics capabilities.
Ease of Deployment and Customer Service: Snowflake is noted for its straightforward deployment in hybrid and public cloud environments, with strong support and effective documentation, though it lacks an SLA. Azure Synapse also supports multiple environments but has mixed support evaluations due to delays, and its integration with Microsoft's broader ecosystem can add complexity.
Pricing and ROI: Snowflake provides a flexible pay-as-you-go model, but its pricing can feel expensive, though it is considered cost-effective over time. Azure Synapse offers competitive pricing within the Microsoft ecosystem but may seem costly compared to other alternatives. Both have complex pricing models, with ROI dependent on scale and system integration.
They are slow to respond and not very knowledgeable.
I received great support in migrating data to Snowflake, with quick responses and innovative solutions.
Microsoft Azure Synapse Analytics is scalable, offering numerous opportunities for scalability.
Snowflake is very scalable and has a dedicated team constantly improving the product.
I find the service stable as I have not encountered many issues.
Snowflake is very stable, especially when used with AWS.
There is a need for more expertise among the support team to guide us effectively.
Cost reduction is one area I would like Snowflake to improve.
Snowflake's pricing is on the higher side.
Microsoft Azure Synapse Analytics offers significant visibility, which helps us understand our usage more clearly.
One key feature is the separation of compute and storage, which eliminates storage limitations.
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:
Microsoft Azure Synapse Analytics Features
Microsoft Azure Synapse Analytics has many valuable key features, including:
Microsoft Azure Synapse Analytics Benefits
Some of the benefits of using Microsoft Azure Synapse Analytics include:
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:
Snowflake has many valuable vital features. Some of the most useful ones include:
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."
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.
