Ably LiveSync is a product we launched last month to help developers deliver live updates in their applications by automatically keeping their database and frontend clients in sync. LiveSync is made of two components, the Models SDK that runs on the client, and the database connector that listens to changes in your database and syncs those changes to your clients.

Handwriting code for database APIs can be a time consuming and expensive process that often exposes organizations to a variety of risks relating to quality, consistency, and developer effort. DreamFactory specialises in REST API generation for a range of databases that gives you the ability to generate a secure, fully documented API in minutes.

A database is a storage system that stores data in an organized manner for easy access and management. In just the last two years, 90% of the world’s data has been created, and the volume of global data doubles every two years. All this data is stored in databases. So, whether you’re checking the weather on your phone, making an online purchase, or even reading this blog, you’re accessing data stored in a database, highlighting their importance in modern data management.

A database schema, or DB schema, is an abstract design representing how your data is stored in a database. Database schemas can be visually represented using schema diagrams, such as the one below: A database schema diagram visually describes the following: Database schemas are at the heart of every scalable, high-performance database. They’re the blueprint that defines how a database stores and organizes data, its components’ relationships, and its response to queries.

Ably’s LiveSync product is now available as a public alpha release. LiveSync allows you to automatically keep data in sync across servers and clients, in realtime. This is a hard distributed systems problem. In this post, we’re going to have a look at four existing solutions to realtime data synchronization, the different technical designs, and the tradeoffs they make.

How to build a flexible pipeline to output Cloud SQL for SQL Server audit records to internal or external sinks with minimal coding in Cloud Data Fusion.

API-database coupling vs. traditional multi-layered architectures: what’s the difference and why does it matter? The main difference between direct API-database coupling and multi-layered architectures is that the former allows the API to interact directly with the database, minimizing latency and complexity, while the latter uses multiple layers to separate concerns.

We count on our database replication connectors for product analytics, and you should, too.

Hey there! We're back for our second edition of Tips and Tricks. As we said in our first post on Drizzle ORM, our new Tips and Tricks mini blog series is going to share some helpful insights and cool tech that we've stumbled upon while working on technical stuff. Today, we're going to talk about the template databases of PostgreSQL. Remember, these posts will be super short reads. If you don’t like the topic of one of the posts, no problem! Just skip it and check out the next one.