Oct, 2022
With the increasing use of SQL Server, database sizes have grown exponentially. There comes a time when tables get so large it is tough to manage and maintain regular backups, perform index maintenance, integrity checks, etc.
Most of the time, archiving the old data helps to keep the database size in check. But sometimes, archiving the database also does not help because it has to be referred to and is required for various purposes. Moreover, running a large, mission-critical database system requires it to be available continuously with minimal downtime for maintenance tasks and backups.
Cloud computing has made it easy to scale. Managing a complex and large database has to be planned as the data grows. If you are running a mission-critical system, SQL Server offers various high availability features with minimal downtime and increases the speed of backup and restore operations.
In this blog, we will cover how to manage large databases efficiently.
Sharding and Partitioning
Sharding and partitioning segregate a large dataset into smaller subsets based on their logical identity. While SQL servers can support hundreds of processors and terabytes of RAM, there is a limit to which data can be stored in a single table. As the database table grows, loading new data, deleting old data, or maintaining indexes becomes challenging. Moreover, the system performance is impacted, and the process takes much longer.
The SQL Server database software provides table partitioning to make such operations more scalable and manageable. The table partitioning is divided horizontally into small units and stored in single or multiple file groups.
Horizontal partitioning is also referred to as sharding when spread across multiple servers. Partitioning divides a large table and its indexes into smaller partitions. It enables:
- Applying maintenance operations on a partition-by-partition basis rather than on the entire table.
- The SQL Server optimizer directs properly filtered queries to appropriate partitions rather than the whole table.
If you do not have the budget, you can leverage third-party services like GeoPITS, which offer managed services, paid consultation, or support for any such work.
Build and Reorganize Indexes to Improve Performance
Maintaining database indexes is one thing every database administrator should care about.Index fragmentation can affect database performance because of many page splits. If you keep adding indexes to the tables to improve performance, but over some time, performance steadily goes down due to the different changes performed on your database data or schema.
Check indexes regularly for fragmentation, then Rebuild or Reorganize them as necessary. The Rebuild operation is time-consuming and cannot be run while users access the database. Therefore, the only way to maintain the indexes on large databases is to Reorganize them. Select the Rebuild option only if the index is corrupted or when there is an absolute need to Rebuild a particular large index.
Indexing should consider the data itself and the types of queries being performed.
- Create indexes based on columns that are being queried.
- Small tables don’t need to be indexed, as they have few unique values.
- Remove unused or underutilized indexes.
- Sort indexes based on how the data is being queried.
Suggested read:Differences between SQL server Index scan and Index seek
Database Normalization
In large databases, data must be organized in tables and linked for easy access and data protection. Lots of data over a period of time become redundant and takes up disk space.
Data Normalization is the process of making the database more flexible by eliminating inconsistencies, errors, and duplications. Database Normalization in SQL also helps remove redundant or repetitive data and ensures data is stored logically. It is done by managing, extracting, and analyzing the information and data flow within the tables or the links between related information. You can retrieve data by SQL statements or by working with other programming languages such as C++, Java, Go, Ruby, etc.
Use Multiple Backup Strategies
Performing backups on large databases could be challenging at times. Because the database log files grow in size, taking backups regularly to save your data is essential. The process can be time-consuming. It would help if you had a backup strategy that can be a continuous process while maintaining data availability.
There are times when the backup might fail because of queries not performing well, workloads running into deadlocks, latency issues, or other disruptions. Using multiple backup devices in SQL Server allows database backups to be written to all devices in parallel.
Similarly, you can easily restore the backed-up data from multiple devices in parallel. Microsoft SQL Server Management Studio provides a Maintenance Plan wizard that allows these tasks to be automated. Use this wizard to create the scheduled tasks.You can also consider third-party tools to reduce the time taken to back up and reduce compressed data size.
Performance Tuning - Keep your SQL Server Environment Current. It is an ongoing process that requires paying attention to all aspects of the SQL Server environment. Performance tuning includes:
- The infrastructure that hosts the environment
- The queries that access the data.
- The indexes that support the queries
- The server and database settings impact performance and more
Microsoft introduces new features that can improve the performance of the database. You should regularly update your SQL Server instances and the underlying Windows operating system to benefit from any recent performance enhancements. It is vital to keep the supporting software and firmware up-to-date. To do this effectively, update a more recent version of SQL Server to remain up-to-date with the new performance-related features.
Suggested read:How to use Database Engine tuning Advisor
Large Database in SQL Server with GeoPITS
Databases require indexing, re-indexing, monitoring, tuning, troubleshooting, fixing, securing, and upgrading the database. GeoPITSoffers a robust database administration service, has been tested and installed hundreds of times, and has provided alarms and notifications to the DBAs, engineers, or DevOps operating the database environment.
GeoPITScan also perform a backup and restore large databases efficiently and easily, providing options to upload them to the cloud (AWS, Google Cloud, and Azure).
If you would like help with managing large databases in SQL Server, get in touch with us.
As an enthusiast and expert in database management, especially within SQL Server environments, I've worked extensively with the challenges and solutions highlighted in the article you provided. Let's break down the concepts discussed:
1. Sharding and Partitioning
These techniques involve dividing large datasets into smaller subsets. Sharding, also known as horizontal partitioning, spreads data across multiple servers, while partitioning divides a table into smaller units. This approach aids in managing and scaling databases efficiently by allowing maintenance operations on a partition-by-partition basis.
2. Index Maintenance
Maintaining indexes is crucial for database performance. Regularly checking for fragmentation and either rebuilding or reorganizing indexes can prevent performance degradation. Creating indexes based on queried columns, removing underutilized indexes, and sorting indexes based on query patterns are key strategies.
3. Database Normalization
Normalization is the process of organizing data in tables to eliminate redundancies and inconsistencies. It ensures logical data storage, reduces redundancy, and facilitates easier access.
4. Backup Strategies
Managing backups for large databases is challenging due to the size and continuous data growth. Implementing multiple backup devices in SQL Server allows parallel backup writing and restoration, ensuring data availability.
5. Performance Tuning
Optimizing SQL Server environments involves attention to infrastructure, query optimization, index management, and staying updated with new features. Regular updates and enhancements to the SQL Server instances and underlying infrastructure are vital for improved performance.
6. GeoPITS and Database Management
GeoPITS offers managed services for database administration, including efficient backup and restore options, monitoring, troubleshooting, and upgrading databases. It provides support for large databases and cloud integration (AWS, Google Cloud, Azure).
The article emphasizes the importance of efficient database management, especially as databases grow in size. It covers essential strategies like sharding, index maintenance, normalization, backup strategies, performance tuning, and the utilization of services like GeoPITS for robust database administration.
The suggestions provided in the article cater to the challenges of maintaining large, mission-critical databases in SQL Server environments, ensuring optimal performance and data availability while managing complexities that come with scaling.
