In SQL Server, there are two types of indexes that can be used to improve performance: row store indexes and columnstore indexes. In this article, we will compare these two types of indexes and discuss their performance improvements.
Row Store Indexes
A row store index is the traditional type of index in SQL Server. It stores data in a row-by-row format, making it efficient for retrieving individual rows or small subsets of data. However, when it comes to scanning large tables or performing aggregations, row store indexes may not be the most efficient option.
Columnstore Indexes
Columnstore indexes were introduced in SQL Server 2012 and have been further improved in SQL Server 2014. Unlike row store indexes, columnstore indexes store data in a column-by-column format. This allows for better compression and faster query performance when scanning large tables or performing aggregations.
Performance Improvements
Let’s take a look at some performance tests comparing row store and columnstore indexes:
Test 1 – Populating Tables
In this test, we populated two identical tables with 30 million rows each. One table had a clustered columnstore index, while the other had a clustered row index and additional non-clustered indexes. The results showed that populating the table with a columnstore index was faster and had fewer logical reads compared to the table with row store indexes.
Test 2 – Comparing SEEK
In this test, we compared the performance of index seek operations on the two tables. The results showed that index seek on a row store index was faster than on a columnstore index. This is because SQL Server does not currently support index seek on a clustered columnstore index.
Test 3 – Comparing SCAN
In this test, we compared the performance of index scan operations on the two tables. The results showed that index scan on a columnstore index was faster than on a row store index. This is because columnstore indexes are optimized for scanning large tables.
Test 4 – Comparing Aggregation Queries
In this test, we compared the performance of aggregation queries on the two tables. The results showed that columnstore indexes performed much better in terms of logical reads and elapsed time compared to row store indexes.
Test 5 – Comparing Updates
In this test, we compared the performance of updating a subset of data in the two tables. The results showed that updating a row store index was faster than updating a columnstore index, although the logical reads for the row store index were higher.
Conclusion
Based on the performance tests, columnstore indexes offer several advantages over row store indexes, especially for scanning large tables and performing aggregations. However, it is important to note that implementing columnstore indexes requires careful consideration of the data warehouse structure and partitioning strategy. Columnstore indexes are particularly useful for large fact tables and can improve the processing time of SSAS cubes.
Overall, columnstore indexes are a powerful tool for optimizing query performance in SQL Server, but they should be used in the appropriate scenarios and with proper planning.