Data-driven organizations are today more of a norm than an exception. Huge volumes of data collected from external and internal sources are collected, processed and analyzed to make accurate business decisions and gain an advantage over competitors. This divergence from traditional manual processes has helped organizations take a quantum leap to optimize and increase operational efficiency.
So what does this all boil down to? Therefore, the call of the hour for organizations is to look for new methods and procedures so that the ultimate goal of processing massive volumes of data can be carried out without the performance of databases decreasing. One of the ways to do this is to move databases to the cloud and take advantage of all the benefits of this comparatively new platform. One way to do this is to move existing databases from SQL Server to Snowflake.
This post will be divided into three parts. The first will be a general overview of SQL Server and Snowflake to understand their features, the second will be the benefits of moving databases from SQL Server to Snowflake and finally how it is done.
Let’s get started.
Microsoft SQL Server and snowflake
SQL Server
Microsoft SQL Server has been among the world’s leading database technologies alongside Oracle and IBM’s DB2. It is completely merged with the complete Microsoft environment and is based on the SQL programming language. All applications support SQL Server on the web, regardless of whether it is a local area network or a standalone system.
Being a relational database management system (RDMS), SQL Server allows users to perform a wide range of complex queries on this system. Additionally, Microsoft offers SQL Server out of the box as part of the MS.NET framework.
Snowflake
Snowflake is a data storage platform that operates in the cloud. It offers users all the advanced technological features normally associated with the cloud. Snowflake and the cloud have been recent innovations, but in a short time they have captured the imagination of users around the world. The reasons are detailed in the following section, demonstrating why businesses today prefer to migrate databases from SQL Server to Snowflake.
Benefits of moving databases from SQL Server to Snowflake
Now we come to the second category and identify the reasons why it makes sense to move databases from traditional on-premises SQL Server to Snowflake.
- Snowflake offers unlimited storage space and users only have to pay for the amount of resources used. In the event of a sudden increase in storage demand, additional resources can be downloaded as needed in minutes paying only for that space. In SQL Server, flat rates apply for specific volumes of storage space, whether it is used or not.
- Snowflake offers high computing power and there is no drop in performance even when multiple users simultaneously run complex queries on the platform.
- Separate computing and storage facilities are available in Snowflake, unlike general databases where it is not possible to differentiate the two. The advantage here is that companies can accurately know the costs individually incurred for storage and computing.
- Data in its native form (structured, semi-structured, or unstructured) can be loaded directly into Snowflake without the need to go through elaborate formatting processes. The same cannot be said for SQL Server. Snowflake offers built-in support for JSON, Avro, XML, and Parquet data.
- There is no need to define indexes before clustering data as Snowflake is a cloud-based platform and is applicable to both column encodings and computing. However, for very large tables, it is necessary to manually use grouping keys to locate the table data.
- Snowflake scales well with a wide range of cloud providers and therefore users do not have to deal with new techniques or technologies when working on databases that have been migrated here.
All of these benefits of working in the cloud are available to companies that migrate their databases from on-premises SQL Server to Snowflake.
Steps to move databases from SQL Server to Snowflake
This process to migrate databases from SQL Server to Snowflake It has four stages.
- Data is extracted from SQL Server using select statements and extract queries that help sort, filter, and limit the data during the mining process. For extracting large databases into text, CSV, or SQL query formats, the Microsoft SQL Server Administration Tool can be used.
- This extracted data is now processed and formatted into a Snowflake-compatible data structure. This process can be skipped for XML or JSON data.
- This processed data cannot yet be dumped directly into Snowflake. Instead, it should be placed in a temporary location which can be internal or external.
Users create an internal staging area directly with SQL statements and assign it a name and timestamp. An external staging area is a default and Snowflake currently supports Amazon Simple Storage Service (S3) and MS Azure.
- The last step in migrating data from SQL Server to Snowflake is to move the data from the staging area directly to Snowflake. For large databases where the data is massive, the Snowflake Data Load Overview tool is used. Run the PUT command to prepare the files first, and then use the COPY INTO command to load the data from the staging area into Snowflake. Snowflake’s Data Load Wizard can be used for small databases.
The entire migration process is fully automated and human No intervention is required at any time.