![]() This helps to reduce the impact on the database’s efficiency and keep disruption to a minimum. ![]() Another added bonus is that this can ensure that your queries aren’t returning as many irrelevant junk results, and may even help with GDPR compliance in the case of databases containing personal information. Large tables can also be partitioned to help stop them from getting too big, and indexes should be monitored to ensure they're still being used any that aren't can be removed to free up additional space.Īre you planning to run any particularly heavyweight queries? It may be worth considering how time-sensitive they are as if it isn’t urgent, it might be worth organising them to run outside of peak business hours when there will probably be less activity on the database. The specifics of what records can safely be deleted and when will depend on the specific purpose of your database, but setting clear data deletion policies can help keep its size to a manageable level. If you’re finding that your database is getting a bit unwieldy, it might be worth seeing if you can streamline it by removing old entries that no longer need to be in there. However, even if you’re restricting database inputs to the bare minimum of fields that need to be there, the size of your database will inevitably swell over time. Retire old or unnecessary dataĪs we’ve just covered, keeping your database streamlined is a key part of making sure they remain efficient and cost-effective. Storing large amounts of infrequently or partially used records can increase the cost and the time it takes to run queries. The best way to ensure that your database doesn’t expand at an unsustainable rate is to set up your schema and validation rules so that it contains only data which is going to be necessary to its operation. Size also plays a factor in process and transaction costs for cloud-hosted databases, or in hardware upgrade cadences for on-premise systems. The bigger it is, the longer it takes to search through it and deliver results from a query. One of the biggest factors that affect both the performance and speed of a database is how large it is. Similarly, using INNER JOINs instead of Cartesian Joins made using WHERE clauses can massively reduce the amount of work being done by the system. ![]() Instead, thinking about the results you’re looking for and structuring your query around those specific fields will cut down on the processing power required to run it. However, this can lead to unnecessary processing if it’s being run on large databases. Using data to drive better outcomes Free Downloadįor example, when selecting fields as part of a query, it can be tempting to use SELECT* to quickly select all records, or using SELECT DISTINCT to identify unique results. Turning data into unmatched business value It also offers more flexibility in porting, replicating and modifying databases, although some may find vertical scaling becomes challenging. For starters, this allows you to host multiple databases on the same infrastructure, which can cut down on licensing and hardware investment costs. If you’re running your databases on single-tenant servers, then porting them to VMs could bring big savings. Virtualisation and multi-tenancy are nothing new in the worlds of enterprise IT and software development, but they can have big advantages for database management. Whichever way you choose to go, automating elements of your database management can help you save both time and money, as well as reducing recovery time in the event of any failures. Many DBAs will choose to write their own custom tools crafted to their specific needs, while others may rely on the automation tools that database management software vendors have built directly into their products. There are many options when it comes to automating database management tasks.
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