This Week in Databend #108

Databend is a modern cloud data warehouse, serving your massive-scale analytics needs at low cost and complexity. Open source alternative to Snowflake. Also available in the cloud: https://app.databend.com .

What's On In Databend

Stay connected with the latest news about Databend.

Multiple Catalogs

Catalog is a fundamental organizational concept in Databend and assists in efficiently managing and accessing your data sources.

Databend allows Multiple Catalogs and currently supports two types of external catalogs: Apache Iceberg and Apache Hive.

With external catalogs, there's no longer a need to load your external data into Databend before querying

-- Create a Hive catalog
CREATE CATALOG hive_ctl 
TYPE = HIVE 
CONNECTION =(
    METASTORE_ADDRESS = '127.0.0.1:9083' 
    URL = 's3://databend-toronto/' 
    AWS_KEY_ID = '<your_key_id>' 
    AWS_SECRET_KEY = '<your_secret_key>' 
);

If you are interested in learning more, please check out the resources listed below.

Code Corner

Discover some fascinating code snippets or projects that showcase our work or learning journey.

Using `cargo-pgo` to Practice PGO

Profile-guided optimization (PGO) is a common compilation optimization technique that utilizes profiling information collected during program runtime to guide the compiler in making optimizations, thereby improving program performance.

According to the tests, PGO boosts Databend performance by up to 10%. The actual performance depends on your workloads. Try PGO for your Databend cluster.

If you are interested in learning more, please check out the resources listed below:

Docs | Profile Guided Optimization (PGO)

Highlights

We have also made these improvements to Databend that we hope you will find helpful:

Introduced the json_pretty function.
Improved performance of Inner Join.
Added more metrics to the HTTP query interface.
Implemented support for SHOW DATABASES and SHOW TABLES in Hive Catalog.
Read Blog | Revolutionizing Data Archival and Query Performance for Pharmaceutical Group to check out how Databend played a pivotal role in transforming data archiving and query performance for a Pharmaceutical Group.

What's Up Next

We're always open to cutting-edge technologies and innovative ideas. You're more than welcome to join the community and bring them to Databend.

Using SQLsmith for Fuzz Testing

SQLsmith focuses on generating random, type-aware and column-aware SQL queries that can often pass semantic checks, thereby further testing the execution logic of databases.

In the past, Databend added support for SQLancer and traditional fuzz testing with LibAFL. The Databend team now plans to introduce SQLsmith for domain-aware fuzz testing, which will provide more comprehensive and targeted test results to increase the likelihood of discovering vulnerabilities.

Issue #12576 | Feature: Using sqlsmith to support sql fuzzy testing

Please let us know if you're interested in contributing to this feature, or pick up a good first issue at https://link.databend.rs/i-m-feeling-lucky to get started.