The Apache Kudu team is happy to announce the release of Kudu 1.10.0!

The new release adds several new features and improvements, including the following:

Kudu now supports both full and incremental table backups via a job implemented using Apache Spark. Additionally it supports restoring tables from full and incremental backups via a restore job implemented using Apache Spark. See the backup documentation for more details.

Kudu can now synchronize its internal catalog with the Apache Hive Metastore, automatically updating Hive Metastore table entries upon table creation, deletion, and alterations in Kudu. See the HMS synchronization documentation for more details.

Kudu now supports native fine-grained authorization via integration with Apache Sentry. Kudu may now enforce access control policies defined for Kudu tables and columns, as well as policies defined on Hive servers and databases that may store Kudu tables. See the authorization documentation for more details.

Kudu’s web UI now supports SPNEGO, a protocol for securing HTTP requests with Kerberos by passing negotiation through HTTP headers. To enable, set the --webserver_require_spnego command line flag.

command line flag. Column comments can now be stored in Kudu tables, and can be updated using the AlterTable API (see KUDU-1711).

The performance of mutations (i.e. UPDATE, DELETE, and re-INSERT) to not-yet-flushed Kudu data has been significantly optimized (see KUDU-2826 and f9f9526d3).

Predicate performance for primitive columns and IS NULL and IS NOT NULL has been optimized (see KUDU-2846).

The above is just a list of the highlights, for a more complete list of new features, improvements and fixes please refer to the release notes.

The Apache Kudu project only publishes source code releases. To build Kudu 1.10.0, follow these steps:

Download the Kudu 1.10.0 source release

Follow the instructions in the documentation to build Kudu 1.10.0 from source

For your convenience, binary JAR files for the Kudu Java client library, Spark DataSource, Flume sink, and other Java integrations are published to the ASF Maven repository and are now available.

The Python client source is also available on PyPI.

Additionally experimental Docker images are published to Docker Hub.