The refined caching mechanisms in Dgraph v24 significantly improve performance by efficiently storing large keys, reducing disk reads, and handling multiple transactions more effectively. The native vector support makes it easier to integrate advanced AI-driven search functionalities into applications. The release also extends DQL and GraphQL by introducing new data types, indexes, math functions, and query functions. The release is a result of the hard work of the Dgraph community, with contributions from 24 different contributors.
Key takeaways:
- Dgraph v24 is now generally available, offering DQL and GraphQL support for Vector data type, HNSW vector indexes, and similarity search.
- The new release includes refined caching mechanisms that significantly boost performance by efficiently storing large keys, reducing disk reads, and handling multiple transactions more effectively.
- Dgraph v24 supports native vector types, making it easier to integrate advanced AI-driven search functionalities into applications.
- The release includes 89 commits from 24 different contributors, highlighting the vibrant community's extensive contributions.