GraphQL and its ecosystem enables Data Federation more easily than before. Hasura Remote Joins Implements GraphQL Data Federation. Let's explore more in this article
Hasura Remove Joins allows developers to use a single data graph to query several underlying data sources. Doing so does not force developers to modify the federated data sources. Developers instead configure the relationships between the federated data models. [The unified GraphQL API], combined with Hasura’s handling of authorization and caching, may provide more consistent and secure data access at scale.
Data sources may expose different interfaces like [GraphQL], [REST], or SQL servers. The [Hasura website] illustrates how federation works. In the illustration, a unified GraphQL query contains data items from several remote sources (a profile id and name come from a Postgres database while addresses comes from a REST resource)
Your Data Architecture: Simple Best Practices for Your Data Strategy. Don't miss this helpful article.
In this post, we'll learn Getting Started With Data Lakes.<br><br> This Refcard dives into how a data lake helps tackle these challenges at both ends — from its enhanced architecture that's designed for efficient data ingestion, storage, and management to its advanced analytics functionality and performance flexibility. You'll also explore key benefits and common use cases.
The agenda of the talk included an introduction to 3D data, its applications and case studies, 3D data alignment and more.
Data Quality Testing Skills Needed For Data Integration Projects. Data integration projects fail for many reasons. Risks can be mitigated when well-trained testers deliver support. Here are some recommended testing skills.
A data lake is totally different from a data warehouse in terms of structure and function. Here is a truly quick explanation of "Data Lake vs Data Warehouse".