GoKawiil
Tech News
ClickHouse announced it has acquired Xata, a company that built copy-on-write database branching technology allowing full database copies to be created in seconds even for multi-terabyte datasets. Xata said existing customers will see no immediate changes and new sign-ups will continue, while the companies work to integrate branching and scale-to-zero features into ClickHouse Managed Postgres, with Xata customers eventually migrated over.
Pivot's engineering team described a new optimization technique that speeds up GROUP BY queries which rank groups by an aggregate value and return only the top results, such as finding the 10 items with the most orders. The post explains how analytical databases like ClickHouse typically execute GROUP BY using parallel threads and partitioned hash tables, then contrasts this with Pivot's improved approach.
The company behind a cloud data warehouse rebuilt its backend around DuckDB five months ago to give customers dedicated instances and a cost-based optimizer. After three months of re-architecting, it says it has removed DuckDB from its stack because customer workloads grew larger and more complex than its single-node, pre-sized instances could handle efficiently.
The pgrust team released v0.4-beta featuring Gravity, a new query engine built with a custom compiler that generates machine code for SQL queries. According to the developers, Gravity runs up to three times faster than ClickHouse on the ClickBench benchmark while still supporting the full Postgres SQL dialect and type system. The engine builds on earlier work using batching, operator fusion, SIMD, and a copy-and-patch JIT compiler.
A developer has released ClickHouse C, a header-only client library written in C11 that decodes the ClickHouse Native wire format, including both the TCP-based Native Protocol and standalone Native Format blocks. The core header works as a pure block decoder with no TCP or compression dependencies, with optional add-on headers providing TCP, compression, codec, and I/O backend support.
A team tasked with speeding up ClickHouse for its largest customers found a critical dashboard query taking over 85 seconds and scanning nearly 2 billion rows across 198GB of data. Over four months, they applied a series of incremental, non-flashy optimizations—tackling issues like the overhead of ReplacingMergeTree's FINAL clause on mutable event data and an inefficient partition key—to bring the query down to sub-second response times.
A Tinybird engineer who has operated ClickHouse clusters since version 18.4 nearly six years ago published a detailed retrospective on running the database at petabyte scale. The post walks through the standard shard-and-replica architecture ClickHouse recommends and highlights the operational pitfalls that only surface once a cluster is running in production. Tinybird notes it is an independent contributor to the open-source project and unaffiliated with ClickHouse, Inc.