Most companies looking for a new data warehouse or analytics platform start their searches with Azure Synapse and Snowflake. Why? - Because these two cloud services support massively parallel processing (MPP), which enables data computation to be distributed over multiple cloud nodes with ease.
The comparison between these two options is inevitable as both these market leaders are growing at a rapid pace. Azure Synapse and Snowflake are two popular and highly recommended ETL technologies for enterprises that need to handle massive amounts of data. Choosing between the two will be based on the qualities and the unique strengths of each service and the needs of your company.
When it comes to data management, Synapse is considered one of the best. Synapse provides an easy-to-use master repository for all forms of data using the Azure Data Lake. All you have to do now is submit your data to the lake and begin constructing your analytics on top of it.
A dedicated and serverless SQL pool are both available in Synapse, enabling you to grow your computational power without regard for storage capacity. The unit of scale for a dedicated SQL pool is a data warehouse unit, which is an abstraction of computer power. Because a serverless SQL pool is serverless, it automatically scales to meet query resource requirements.
Snowflake is a lot easier to set up and operate, and the zero-copy cloning feature is always beneficial. Snowflake's automation is what sets it apart from the competition. Database optimization, partitioning, and indexing, among other things, can be all done automatically, which implies less time wasted on data warehouse administration. Snowflake also has a fee system that is dependent on usage. You will not be charged if you choose not to use Snowflake.
Snowflake's costs are calculated on a per-second basis and are billed on a pay-as-you-go basis. The minimum duration of time required to auto-suspend and auto-resume operations is 60 seconds. So, if your query takes three minutes to process, you'll only be charged for three minutes if the virtual data warehouse is suspended after the query is finished.
Azure Synapse, on the other hand, charges on an hourly basis for computing. As a result, if your data warehouse is only operational for 12 hours every month, you will only be billed for those 12 hours. Even if the data warehouse is only active for 30 minutes, you will be charged for an hour.
When it comes to scalability, Snowflake dominates due to its multi-cluster and shares data design. Snowflake allows you to isolate diverse workloads into a common data layer at the same time. You can also employ Virtual Warehouses to achieve unrestricted growth and concurrency while avoiding downtime.
Both dedicated SQL pools and serverless SQL are available in Azure Synapse. The former has a per-defined scale unit (called a Data Warehouse Unit (DWU)), whereas the latter scales automatically to match your scaling requirements.
Snowflake's main goal has always been to require minimal maintenance. This is fantastic news for data managers because it eliminates the need to recruit and train a specialized Snowflake account manager. It is user-friendly and thrives on automated solutions.
The admin side of things will be much more involved with Azure Synapse. Because performance monitoring is not automated, everything from tuning to concurrency control will require human intervention.
When it comes to administration, Snowflake is the clear victor because it is as close to hands-free as it can be.
Performance and Future-proofing is another area where the similarities between Azure Synapse and Snowflake make it tough to choose between the two. Both are ultra-fast, cutting-edge MPPs that provide real-time data access.
Both Synapse and Snowflake continue to evolve, but neither has forgotten about the cloud's core requirements. Both have put in a lot of effort to set the bar for data warehousing.
The following are some of Azure Synapse's limitations:
If you've never used it before, there'll be a steeper learning curve.
Queries that span multiple databases are not supported by Azure Synapse.
The setup procedure is lengthy.
The following are some of the Snowflake's limitations:
Some database use cases, such as online transactional processing situations, are not suitable for it.
For newbies, Snowflake might be challenging to utilize.
The user interface is not user-friendly.
Snowflake is too pricey for most users and small businesses.
There isn't much of a difference between the two most popular MPPs in the market. Both are highly optimized, simple to use, and capable of handling large workloads.
Snowflake should be considered before Azure Synapse for small-sized businesses with significant growth expectations. It's made to make scaling easier, which can save you a lot of time and effort. Azure Synapse, on the other hand, is what you should be looking at more closely for larger businesses.