During development, it’s important to think about how your application will work with your databases. You can run into performance issues all the way through the stack, so you’ll want to be mindful of how the data is being accessed. From the client to the database, there are layers where trouble may creep in. Here are database performance issues you might encounter...
Database and data warehousing technologies are evolving at a tremendous pace. Businesses are increasingly diversifying their critical data across multiple databases to remain competitive and capture the technical innovation each database vendor provides. With data modernization (and digital transformation), a key initiative for many organizations, leveraging the power of databases — particularly massively parallel processing cloud-based databases — is the new normal.
MySQL is a popular open-sourced relational database server. It comes in many flavours, including Enterprise and Community editions. Amazon Web Services, Microsoft Azure, and Google Cloud Platform all provide their own managed MySQL services. The available versions and features vary from provider to provider. As an added complexity, AWS provides three different MySQL services, each one of them different. Let’s take a closer look.
Grafana by default uses sqlite3 as a local database to hold the configuration information (such as users, dashboards, alerts, etc.). But did you know you can also use other databases for this purpose? Many large customers prefer to use either Postgresql or MySQL/MariaDB, and we recently had a request from a company wanting some help to migrate their configuration data from Postgresql to MySQL. This is not a common request, so we didn’t have any pre-existing tooling to do it.
In this article, we are going to build together, step by step, a cache layer using Redis and add it to an existing Node application. If you have a Node web server that uses MongoDB via `mongoose` and you would like to add a cache layer to optimize your queries, I hope this article will help you reach your goal. To run this application locally you need to install docker on your machine if you are not familiar with docker and docker-compose you should visit docker official website.
Redis is an extremely fast NoSQL data store. While it is used mainly as a cache, it can be applied to uses as diverse as graph representation and search. Client libraries are available in all of the major programming languages, and it is provided as a managed service by all of the top cloud service providers. For the past three years, Redis has been named the most loved database by the Stack Overflow Developer Survey.
Software of all kinds requires information to do its work. At the back end of most programs you’ll usually find some form of database, which has been created or selected and configured to run specifically with that application. In creating that database or making a selection from the wide range of products available, there are several factors to consider. We’ll be looking at these criteria, in this article.
MongoDB is no different from other databases as in the fact that it relies on data replication, and even if we had quantum computers at our disposal, there will always be at least a small amount of lag when replicating operations from the primary to secondary node. MongoDB replication lag is specifically the interval of time from when an operation is run on an application in the primary node, and the operation being applied to the application on the secondary node from the oplog.
LogicMonitor recently released 15+ new DataSources and 2 PropertySources for Oracle Database monitoring. This release is our most extensive update to the Oracle platform yet. With this update, we include support for multi-database configurations and containerization.
