Choosing the right method to store your data can be a critical decision early in the development process. When deciding on which type of database to choose for your project it really comes down to the data structure you wish to use rather than the specific product or provider. In this blog post, we are going to look at relational and non-relational databases and explore the differences and use cases for both.
The time has come for the open-source software revolution to reach SQL.
Thirty five years ago, SQL-86, the first SQL standard, came into our world, published as an ANSI standard in 1986 and adopted by the International Standards Organization (ISO) in 1987. On this Valentine’s Day, we, in BigQuery, reaffirm our love and commitment to user-friendly SQL through a whole slew of new SQL features that we’re pleased to share with you, our beloved BigQuery users.
Most web applications use a data store of some kind, often a relational database. When a web app becomes successful, it can become all too easy to start "hoarding" data in the database. But hoarding data leads to the unbounded growth of database tables (both row count and stored data size). While this works fine to a certain point, it is very useful to prevent some data bloat — or, if you cannot prevent it, to plan for your infrastructure ahead of time to adequately manage growth.
Starting with the 2.7 release, using Cassandra as a configuration datastore for the Kong Gateway will be considered deprecated. Cassandra features will remain in Kong throughout the (currently unreleased) 3.x series, and its use will not be prohibited. However, some newly introduced functionality throughout 3.x may not be optimized for performance or have full functionality when using Cassandra.
When enterprises and companies are having trouble with SQL query optimization, they frequently turn to performance tuning tools and optimization strategies. This will not only help in analyzing and speeding up queries, but also in resolving performance issues, troubleshooting bad performance, and avoiding or minimizing the impact on SQL Server databases. Data accessibility, availability, and performance are critical to corporate success.
In this article, you will learn how to test database performance in Rails and solve some of the most common database performance issues. When you develop a Rails application, ActiveRecord is the default tool that manages your database. ActiveRecord provides an easy and fast interface to query and insert data using commands like.where, .save, .create, and.update. Rails does the work of converting these commands to SQL queries, which is a good thing, but sometimes can cause performance issues.
This short post by a member of Ably's engineering team describes how we resolved a problem that is typical of the challenges we face each week. We thrive on solving hard distributed system problems that are mostly platform agnostic and theoretical in nature, and this is the first post in a long-term series of articles about things we've learned recently.
SQL performance tuning is a difficult task, especially when working with large amounts of data, where even slight changes can have a significant (positive or negative) influence on performance. A Database Administrator (DBA) will be in charge of most SQL performance adjustments in mid-sized and large businesses. However, believe me when we say that there are plenty of developers that have to perform DBA-like jobs.
