Pre-Release of Polars 2.0
Preview of Python Polars 2.0, bringing the streaming engine to all lazy queries
The latest blog posts to take off on Hacker News. 2,337 posts.
Preview of Python Polars 2.0, bringing the streaming engine to all lazy queries
A new wave of litigation focused on violations of municipal regulations is emerging against multifamily housing landlords, many of whom are facing antitrust litigation targeting their use of certain revenue management products. The new regulations may potentially provide a simpler path to liability and the possibility…
Quick reference guide for transforming, analyzing, and visualizing data with Python Polars.
DuckDB 2.0 is coming this fall. In this post, we preview its headline features: DuckDB as a server, triggers, the VARIANT type, asynchronous I/O, a new SQL parser, a new storage format, and much more.
I did this from a lawn chair on the Sunshine Coast.
SpaceXAI returns to the intelligence frontier with strengths in agentic performance and cost efficiency
Tailscale and SQLite developers traced maddening corruption incidents to find the WAL-Reset data race, then uncovered a second stale expression index bug.
Starting with v2.0, scheduled for fall 2026, DuckDB will support asynchronous reads of Parquet and CSV files. This can significantly speed up queries when synchronous I/O does not saturate the available bandwidth, as is typical in EC2/S3 compute-storage setups.
Discover Snowflake Postgres Mirroring. Learn how push-based change data capture delivers transactional replication to your data lake with zero lag.
How we used SKIP LOCKED, composite primary keys, and connection visibility to hit our scale targets.
The Black Hole Mapper reaches a milestone with its first southern hemisphere optical observations, coordinated eROSITA X-ray identification, and multi-epoch tracking of accreting black holes across the universe.
A 4B open-source model post-trained with Castform retrieved search results as accurately as GPT-5.6 Sol, while costing 100x less.
A well-written, *FAST* data science database for your laptop.
I am excited to announce that I am joining ClickHouse, Inc. to establish and lead a new research team at ClickHouse Labs.
PlanetScale backs up petabyte-scale sharded Postgres databases in hours using parallel infrastructure, object storage, and WAL replay.
Lessons learned from scaling Postgres-backed durable queues for users running tens of billions of workflows per month.
A recap on the work done in NumPy and CPython to make multi-threaded NumPy workloads scale on the free-threaded build of CPython.
Transitioning SQLite from a local development tool to a production-grade database requires a deep understanding of its internal mechanics. This article explores how to tune WAL mode, manage busy handlers, and leverage custom Virtual File System (VFS) layers to achieve ultra-low latency.
How we optimized Postgres LISTEN/NOTIFY-backed data streams to 60K writes per second on a single Postgres server, with millisecond-scale latency.
A guide to preventing Postgres from toppling over.
Turso is becoming the LLVM of databases: one modern, reliable Rust core with many SQL frontends. After rewriting SQLite, we are now building Postgres.
How to make 768 distinct Postgres servers look like 1 to your applications.
PgBouncer is single-threaded, so a single process caps out at one CPU core no matter the box size. See how ClickHouse Managed Postgres runs a peered fleet of PgBouncer processes with so_reuseport to scale pooling across every core — with benchmarks showin
A real quarter of UK SME books, 59 transactions, 68 minutes, $2.73 of tokens — and a VAT return within 7 pence of the human-prepared one.
Pruning agent context down to what the answer actually needs, while keeping 96% of recall
In this blog post, we will explain how strict memory overcommit protects your database from catastrophic OOM (out of memory) kills. We will also share how a one character kernel bug forced us to temporarily disable this setting. Finally, we will explain our heuristic for determining the right memory overcommit limit…
Keeping workflow state and application data in the same Postgres database lets one transaction update both, simplifying idempotency and atomicity.
Almost every traditional database keeps its write-ahead log and data files on one machine's disk, which is the root cause of data loss risk, expensive read replicas and high-availability clones, and analytics queries that drag down transactions.