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Announcing DuckDB 2.0.0 LTS “Cinnamon Teal”
The DuckDB team announces DuckDB 2.0.0 LTS, its biggest feature release so far: a polished Quack protocol for DuckDB as a server, asynchronous I/O, a first-class VARIANT type, agent mode, triggers, an extensible PEG-based SQL parser, plus breaking changes and migration notes.
12 min · 2,753 words
Can we replace a $150k Looker with a bucket of HTML files?
A three-person data platform team describes how an afternoon side project for hosting AI-generated HTML reports grew to rival their $150k-a-year Looker deployment in weekly users, and when building beats buying enterprise BI.
12 min · 2,796 words
The Polars team ships Polars 2.0: initial out-of-core spill-to-disk support on by default, core engine and optimizer speedups, first-class SQL that leads DuckDB and DataFusion on TPC-H and TPC-DS style benchmarks, a new Map dtype, and stricter dtype handling, plus a detailed benchmark appendix.
6 min · 1,287 words
Accelerated Out of Core Shuffling
Benjamin Zaitlen explains RapidsMPF’s reusable out-of-core shuffler for distributed analytics—how spilling turns shuffle OOM headaches into a budgetable resource, and what it takes to push shuffle bandwidth toward terabytes per second.
15 min · 3,466 words
What happens when you analyze college football like the CIA?
What happens when you analyze college football like the CIA? A couple weekends ago, the Illinois football team lost to Duke at home, 31–27.
11 min · 2,518 words
Inline vs. Separate Tables for Vectors in Postgres: Measuring the Join Overhead
Separate Tables for Vectors in Postgres: Measuring the Join Overhead Testing semantic search, filtered queries, and multi-table joins in AlloyDB to measure the true cost of decoupling your vectors.
10 min · 2,296 words
Ghost Jobs Report, September 2026
Unlisted finds 28.3% of 607,050 career-site job postings have been open over 90 days—age by category, country, ATS, and the employers with the most stale listings.
7 min · 1,617 words
Writing Parquet Files Using Haskell
A practical walkthrough of generating Apache Parquet from Haskell: schema encoding, column chunks, and the tradeoffs of building interoperable analytical data files outside the JVM ecosystem.
11 min · 2,537 words
Aleksandar Filipovski, 2026-09-16 See also: John Salvatier’s excellent blog, Reality has a surprising amount of detail I read a comment somewhere that stuck with me, that went something like this:
8 min · 1,784 words
The query finished… Why is my Fabric SQL database still consuming CUs?
Two minutes of SQL database activity in Microsoft Fabric can mean ~17 minutes of compute billing. Nikola Ilic walks through CU metering with application, development, and troubleshooting examples.
8 min · 1,796 words
Beyond the model: Engineering AI infra with scientific judgementHow Airbnb's agent harness encodes scientific methodology for unstructured data exploration.
Ask a coding agent to analyze 100,000 customer support conversations and within minutes you’ll have a polished taxonomy, precise prevalence numbers, and an executive-ready summary. What you can’t see is the investigation that produced them: the methods it chose, the evidence it weighed, how much to trust it, or whether a second request would agree. All that reaches you is the polish. The model is undeniably intelligent, but intelligence without methodology is not science.
5 min · 1,106 words
Same Job, Two Engines: InnoDB and Iceberg Internals
Marc Paul compares running the same stock-analysis workload on MySQL InnoDB (OLTP) and an Iceberg lakehouse (OLAP): what InnoDB optimizes for, and the two mechanisms that make a lakehouse work — read-side pruning and the atomic pointer-swap commit.
14 min · 3,128 words
LLM Classification Is Feature Engineering
Taylor Pospisil argues LLMs work better as feature generators than as end-to-end classifiers, covering calibration, thresholding, cost, and how to treat model outputs as engineered features.
13 min · 3,039 words
Eddie argues that Pandas forces data practitioners to adopt distributed compute infrastructure long before their data sizes justify it, and that DuckDB and Polars can fill the gap for workloads up to around 100 GB on a single machine. Benchmark results show Polars and DuckDB completing a one-billion-row task in under a minute, while Pandas takes over twelve.
1 min · 268 wordsagent-written
MotherDuck's Mehdi Ouazza benchmarks the DuckDB 2.0 alpha on a laptop and S3, covering async I/O read-ahead that makes S3 reads 2-3x faster with no query changes, faster recursive CTEs for deep hierarchies, shredded VARIANT columns that beat JSON parsing about sixfold, and smaller wins from the commit log.
10 min · 2,220 words
Planet Labs' Open Satellite Feed
Mark Litwintschik surveys Planet Labs' satellite fleet and walks through practical use of the company's freely available Disaster Data feed, which publishes pre- and post-event imagery from natural disasters as DuckDB-friendly Parquet files hosted on Cloudflare.
1 min · 260 wordsagent-written
Introducing chdb Postgres extension: High-performance imports from cloud storage
ClickHouse announces the chdb Postgres extension: fast imports and exports across cloud storage and formats, powered by the embedded ClickHouse engine and usable via COPY-style workflows.
7 min · 1,599 words
Polars is releasing its first 2.0 release candidate, with the major change being that all LazyFrame queries now default to the streaming engine, delivering substantial memory and performance improvements for most users. The version bump is driven by breaking changes to defaults rather than new features, and a migration guide is provided.
1 min · 269 wordsagent-written
No Easy Fix for Bogus Respondents in Online Opt-In Polls
Pew Research Center tests trap questions, CloudResearch Sentry, and voter-file matching on 11,114 opt-in respondents: bogus cases still distort quality, and voter-file matching can raise error by discarding valid people.
16 min · 3,670 words
I've operated petabyte-scale ClickHouse clusters for 5 yearsWhat I learned operating ClickHouse at scale: the wins, the failures, and the lessons that only come from production experience.
Tinybird co-founder Javi Santana shares five years of operational experience running petabyte-scale ClickHouse clusters, covering architecture decisions, the challenges of storage-compute separation, zero-copy replication trade-offs, and how the upgrade process evolved from a three-hour ordeal into a CI/CD-integrated routine.
1 min · 280 wordsagent-written