In this post, we will look at how to take a backup of your Heroku Postgres DB and Hasura Metadata / Migrations so that you can migrate to a different DB vendor.

We recently announced the general availability of BigQuery in Hasura! Now you can connect a BigQuery database to your Hasura application to consume data.

Today we’ve released the alpha of the Hasura GraphQL Data Connectors as open source. This is a combination of an API Agent, an SDK to develop against that agent, and a reference application to show a working example of how it all works to provide new connections to varied data sources.

Hasura Learn comes with 25+ open source tutorials on GraphQL, Databases & Hasura to help developers get up to speed with these technologies.

Last year November's release of TypeScript was one of the most exciting releases. Literal types took over the TypeScript community by opening a whole new set of possibilities.

The release of Hasura 2.0 included one of the most exciting features to date - multiple database backends, and in particular, support for our first new backend, Microsoft SQL Server. On the face of it, this probably seems like a relatively straightforward change.

Today I've collected together a number of video shorts, extra details, and information about primary keys, primary key data types, and data types in general. In this post I've included links to mapping from Postgres types to JavaScript types via GraphQL and Hasura.

Another new feature exclusive to the Hasura 2.0 release is support for multiple Postgres database types. In just a few clicks you can add an an extra database, existing or new, track the tables, enable relations, and unlock the power of GraphQL.

Performance and High availability are critical challenges in production. Although TimescaleDB solves performance problems, we still need to care about remaining parts. In this article, I suggest some high availability setup for single-node as well as explore multi-node replication solutions.

Multi-node is the most interesting feature of version TimescaleDB 2.0 that provides the ability to create a cluster of TimescaleDB instances to scale both reads and writes.