When it comes to data storage, you have two main options: SQL Server and Snowflake. Each has its own advantages and disadvantages, so it's important to consider your needs before making a decision. SQL Server offers more control, but Snowflake offers simple management. With Snowflake, you can easily handle structured and unstructured data such as JSON and XML files, and store it in relatively cheap cloud file storage such as Amazon S3 or Azure Blob Storage.
Plus, you can query all your data with ANSI SQL. On the other hand, SQL Server data warehousing can get stuck in a quagmire of resource contention when it tries to juggle all the competing tasks imposed on it by a business intelligence solution. You may also find that you're trying to send too much data and processing through the SQL Server engine, making you want to move from an SQL server to Snowflake. Snowflake is a cloud-based data platform that allows users to scale, use all their data and support all users instantly and automatically, share data securely, control costs, access data from any cloud and query all data with ANSI SQL.
It can help you overcome some of the common problems you may have with SQL Server. To help determine if your data needs have matured beyond MS SQL, we've identified five common data problems: how Snowflake solves them and whether you need a migration from SQL Server to Snowflake.
- Server virtualization and scaling of Azure SQL Server allow scaling up or down as needed, but managing the process can be cumbersome.
- Data warehouse downtime can be time consuming.
- Too much data and processing can be sent through the SQL Server engine.
- Data needs may have matured beyond MS SQL.
- Data management can be modernized with Snowflake.
But if you want simple management and scalability, then Snowflake is the way to go.
