Hasura is looking beyond solely transactional databases with its new platform update, enabling users to more easily connect with BigQuery as well as other data sources.
Hasura on Feb. 23 released the 2.0 version of its namesake GraphQL platform, providing users with new capabilities to enable data connectivity and access.
GraphQL is an open source query language commonly used to enable APIs to connect with various data sources including databases. The core GraphQL specification effort is led by the GraphQL Foundation, of which Hasura is a founding member. The Hasura GraphQL platform is also open source, with a managed service offering available via the Hasura Cloud, which became generally available in July 2020.
With Hasura GraphQL Engine 2.0, the vendor, based in San Francisco, is expanding its platform to enable support for REST APIs alongside GraphQL APIs, providing users with more options for connecting data sources. The new Hasura update now also enables connectivity with more data sources, including Microsoft SQL server as well as Google BigQuery.
Among Hasura's users is Close Matrix, vendor of a service to help enable business deal closings that require signatures. Max Cantor, co-founder of Close Matrix, said Hasura fills a critical role in his company's systems.
Close Matrix runs Hasura on the AWS cloud, with RDS Postgres serving as the data layer, with a front end that uses the React TypeScript JavaScript framework.
Hasura eliminates the need for 90% of the back-end glue code we'd otherwise have to write. For a small dev team, this code savings is what allows us to move quickly to serve our customers.
Max CantorCo-founder, Close Matrix
Cantor explained that Hasura helps to create the "glue code" that connects different elements to enable his company's service to work. That glue code provides the query layer between the database and the front-end react code running in his customers' browsers. Hasura also enables authorization logic, which dictates what data can be viewed and updated and by whom.
"Hasura eliminates the need for 90% of the back-end glue code we'd otherwise have to write," Cantor said. "For a small dev team, this code savings is what allows us to move quickly to serve our customers."
Hasura GraphQL Engine 2.0 features
While GraphQL is the foundation for Hasura, Tanmai Gopal, co-founder and CEO of Hasura, noted that many organizations rely on REST APIs and tooling to connect with data and services.
Gopal explained that Hasura GraphQL Engine 2.0 will now enable users to create a GraphQL-based service that provides access to data that can also be queried by other tools and services as a REST endpoint. The idea is to enable organizations to continue using existing REST-based tooling they already have, while creating new endpoint data connections with GraphQL, Gopal said.
A GraphQL-based endpoint offers several advantages over one created in REST, including performance and resource optimization.
The Hasura GraphQL Engine 2.0 architecture enables users to securely access and query different data sources including Microsoft SQL Server as well as Google BigQuery.
Security improvements
The new Hasura GraphQL update also gets improved security capabilities.
Gopal noted that the release provides authorization and security rules to GraphQL as it is connected to different data sources. The authorization capabilities include integration with user policy technologies including Microsoft Active Directory.
"We're making it easier for mission-critical enterprise environments to be able to secure their GraphQL services," Gopal said.
Hasura adds data connectivity options
Hasura GraphQL Engine 2.0 make it easier for users to connect with Google BigQuery, which is used for analytics workloads.
Adding support for BigQuery is a bit of a departure for Hasura, which had previously been focused mostly on transactional and OLTP (online transaction processing) type databases and sources, Gopal noted. BigQuery, in contrast, is an OLAP (online analytical processing) system, an area in which Hasura may provide even more support in coming releases.
"Based on the feedback that we see from this release, we see ourselves expanding our OLAP footprint as well, and supporting other data lakes and data warehouses," Gopal said.
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