Databases are everywhere these days, every application uses databases to store, organize and retrieve data. It has become more efficient than paper storage since it does not require more space and can also be easily accessed by multiple users at a time. There is an increase in demand for processing vast collections of data and this has become the most important reason for several companies to use databases.
Choosing whether to go with PostgreSQL or MySQL depends on your needs as they are both great databases to use under different circumstances. In this article we will run through a few of the top reasons and use cases to help you choose between these choices for database creation. Note: As a matter of fact, MySQL is so popular it became part of the LAMP stack (Linux, Apache, MySQL, PHP) used for building many web servers.
During data analysis in SQL, one will often need to look at multiple tables and join them to get the desired results. Joining tables for analyzing data is a required skill for a data scientist or data engineer. Selecting the right join will optimize query performance.
When running any performance benchmarking tool on your cluster, a critical decision is always what data set size should be used for a performance test, and here we demonstrate why it is important to select a “good fit” data set size when running a HBase performance test on your cluster.
In this article, we'll see how to use Airtable to store realtime messages using a group chat app as an example. We'll use Ably's realtime infrastructure to power the chat app and make use of WebHooks to publish messages to Airtable directly in the correct order from Ably. Check the full source code of the group chat app written in VueJS on GitHub and the live demo of the application at https://realtime-chat-storage.ably.dev/
We’re excited to share that after adding ANSI SQL, secondary indices, star schema, and view capabilities to Cloudera’s Operational Database, we will be introducing distributed transaction support in the coming months. The ACID model of database design is one of the most important concepts in databases. ACID stands for atomicity, consistency, isolation, and durability. For a very long time, strict adherence to these four properties was required for a commercially successful database.
Key differences between Hive and SQL: Big data requires powerful tools. Successful organizations query, manage and analyze thousands of data sets from hundreds of data sources. This is where tools like Hive and SQL come in. Although very different, both query and program big data. But which tool is right for your organization? In this review, we compare Hive vs. SQL on features, prices, support, user scores, and more.
AppSignal was built because we were tired of slow and clumsy monitoring setups. Instead, we built monitoring that’s easy yet powerful - an intuitive interface enables you to figure out what’s happening in no time. Today, our team made finding slow events effortless. We’ve fully overhauled our slow events feature, helping developers to quickly find and fix slow queries and API requests.
In this blog post, let us take a look at how you can plan your infrastructure planning that you may have to do when deploying an operational database cluster on a CDP Private Cloud Base deployment. Note that you may have to do some planning assumptions when designing your initial infrastructure, and it must be flexible enough to scale up or down based on your future needs.
