Databend aimed to be an open source elastic and reliable cloud warehouse, it offers blazing fast query and combines elasticity, simplicity, low cost of the cloud, built to make the Data Cloud easy.

Big changes

Below is a list of some major changes that we don't want you to miss.

Features

  • databend-query: external source with new processor: make external source(like S3) as table engine. by @BohuTANG, (#4277)
  • functions: support EXTRACT && toYear by @clark1013, (#4329)

Improvement

  • databend-query: add more metrics into query_log table: io metrics of dal level. by @sundy-li, (#4365)
  • databend-meta: refactor role identity: remove host for role identity. by @Junnplus, (#4370)
  • databend-query: refactor the comparison function by using ScalarBinaryExpression by @zhyass, (#4285)
  • databend-query: add CALL command: impl CALL syntax parser, add Trait for system function. by @Junnplus, (#4315)

Performance Improvement

  • datablocks&datavalues: support nullable group by: improved by 60% on the second query with metacache. by @sundy-li, (#4340)
  • datablocks: use `SmallVec`` to improve HashMethod Serialize: improved by 30%~50% in ontime dataset. by @sundy-li, (#4353)
  • datavalues: Simd Selection of column filter: improved by ~25%. by @platoneko, (#4271)

Bug fixes

Tips

Let's learn a weekly tip from Databend.

RFC: Semi-structured Data Types

Semi-structured data types are used to represent schemaless data formats, such as JSON, XML, and so on. In order to be compatible with Snowflake's SQL syntax, we plan to support the following three semi-structured data types:

  • Variant: A tagged universal type, which can store values of any other type, including Object and Array.
  • Object: Used to represent collections of key-value pairs, where the key is a non-empty string, and the value is a value of Variant type.
  • Array: Used to represent dense or sparse arrays of arbitrary size, where the index is a non-negative integer (up to 2^31-1), and values are Variant types.

For more information see Semi-structured data types design. For ongoing work see databend#4348.

Changlogs

You can check the changelogs of Databend nightly to learn about our latest developments.

Meet Us

Please join the DatafuseLabs Community if you are interested in Databend.

We are looking forward to seeing you try our code. We have a strong team behind you to ensure a smooth experience in trying our code for your projects. If you are a hacker passionate about database internals, feel free to play with our code.

You can submit issues for any problems you find. We also highly appreciate any of your pull requests.