In one of my recent assignments, my client asked me for a solution, to reduce the disk space requirement, of the staging database of an ETL workload. It made me study and compare the Table Compression feature of SQL Server. This article will not explain Compression but will compare the storage and performance aspects of … Continue reading Storage savings with Table Compression
Author: Brahmanand Shukla
Estimating the storage savings by removing columns with NULL value across the table or marking them as SPARSE
In the previous article Find columns with NULL values across the table we discussed that storage space can be saved by removing columns with NULL value across the table or marking them as SPARSE. We also learnt about the query to find all such columns across the tables of a database. In this article we'll … Continue reading Estimating the storage savings by removing columns with NULL value across the table or marking them as SPARSE
Find columns with NULL values across the table
Recently, I was working on one of the performance tuning assignment with an esteemed client. The size of their databases were growing tremendously. Growth in the database size is directly proportionate to disk space requirement. More the database size will be, more disk space will be required. When we talk about the disk space for … Continue reading Find columns with NULL values across the table
Tracking costliest queries
Being a Database Developer or Administrator, often we work on Performance Optimization of the queries and procedures. It becomes very necessary that we focus on the right queries to get major benefits. Recently I was working on a Performance Tuning project. I started working based on query list provided by client. Client was referring the … Continue reading Tracking costliest queries
Probing Columnstore Indexes
This article was first published on: 2020-03-14. This article will probe the performance benefits of columnstore indexes, on a transactional (OLTP) workload for real-time analytics. We'll cover examples from each of the followings - Pivot, Aggregate Functions, Analytic Functions, Ranking Functions and Window Functions.