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In the world of big data, the ability to quickly and efficiently analyze large datasets is vital. SQL Server 2016 introduced a significant feature to help with this task: Columnstore Indexes. This type of index stores column data together, as opposed to traditional row-based storage, offering a huge boost in querying and analytics performance. In this post, we'll explore the real-world use of Columnstore Indexes in SQL Server 2016.

A key advantage of Columnstore Indexes lies in their ability to compress data, allowing for more efficient use of memory and faster query execution. This makes them ideal for large OLAP (Online Analytical Processing) workloads where large volumes of data need to be analyzed and aggregated. For example, you could use a Columnstore Index to quickly analyze sales data across a multinational corporation.

Creating a Columnstore Index in SQL Server 2016 is straightforward. Here's an example of how to create a non-clustered Columnstore Index on a table:

CREATE NONCLUSTERED COLUMNSTORE INDEX ix_yourIndexName
ON yourTableName (yourColumnNames);

While Columnstore Indexes were introduced in SQL Server 2012, SQL Server 2016 significantly enhanced them with the ability to be updatable and to use them in operational analytics. In SQL Server 2017, this feature was further improved with the introduction of auto-managed Columnstore Indexes, which automatically handle index defragmentation, offering an even more hands-off, efficient experience.

It's worth noting that Columnstore Indexes are not unique to SQL Server. Similar technologies exist in other database systems. For instance, MySQL 5.7 introduced InnoDB as a storage engine that supports compressed columnar storage, and DB2 11.1 also offers BLU Acceleration for column-organized tables, providing similar performance improvements.

For those utilizing Azure SQL, Columnstore Indexes are fully supported. Azure SQL is essentially SQL Server hosted in the cloud, so the same Columnstore Index techniques and benefits apply. This makes it possible to handle massive amounts of data in a cloud-based environment without sacrificing performance.

To sum up, Columnstore Indexes in SQL Server 2016 and beyond represent a powerful tool for handling big data. They allow for faster querying and data analysis, making them a key asset for any data-driven business. Whether you're using SQL Server 2016, SQL Server 2017, MySQL 5.7, DB2 11.1, or Azure SQL, you'll find Columnstore Indexes or similar technologies ready to help you manage your data more effectively.