Every #TimeSeriesDatabase is just a set of storage decisions:
➡️ Row layout
➡️ Compression timing
➡️ Partitioning strategy

These choices often impact cost and query performance more than the database you pick.

This #InfoQ article breaks down these fundamentals from first principles using #PostgreSQL & #ApacheParquethttps://bit.ly/4fkDHlV

#BigData #TimeSeriesData #Database

Announcing the first ever Apache Arrow and Parquet meetup in Paris, kindly hosted by @datadoghq .

If you’re using Arrow or Parquet, looking for insights, or wanting to meet other community members, this meetup is for you. Please register if you plan to attend!

https://luma.com/6ed1oko1

#apachearrow #apacheparquet

Apache Arrow / Parquet - June 2026 meetup in Paris · Luma

Details We’re excited to announce the first ever Apache Arrow and Parquet meetup in Paris! This meetup will be hosted on June 18th by Datadog, in their…

Hardwood: A New Parser for Apache Parquet

Today, it’s my great pleasure to announce the first public release of Hardwood, a new parser for the Apache Parquet file format, optimized for minimal dependencies and great performance. Hardwood is …

Gunnar Morling
Apache Parquet vs. Newer File Formats (BtrBlocks, FastLanes, Lance, Vortex)

For over a decade, Apache Parquet has been the cornerstone of analytical data storage. Parquet emerged in the Hadoop era as an open…

Medium
Feature: disable HMR/watchers in the CLI, with other useful development features by diraneyya · Pull Request #3201 · evidence-dev/evidence

Summary This PR enhances Evidence's development experience and proxy support with several improvements to CLI options, configuration, and developer workflows. Key changes Proxy Support: Added ...

GitHub

https://blog.ronandev.ovh/apache-parquet/

Apache Parquet est le format de stockage colonnaire incontournable pour le Big Data. Optimisé pour la performance et la compression, il accélère les requêtes et réduit les coûts. Intégré à Spark, Iceberg et les architectures lakehouse, Parquet offre interopérabilité et efficacité.

#ApacheParquet #dataengineering

Apache Parquet : Le format de stockage incontournable pour le Big Data

Apache Parquet est le format de stockage colonnaire incontournable pour le Big Data. Optimisé pour la performance et la compression, il accélère les requêtes et réduit les coûts. Intégré à Spark, Iceberg et les architectures lakehouse, Parquet offre interopérabilité et efficacité.

Le blog de Ronan | Data Engineer
GitHub - cwida/FastLanes: Next-Gen Big Data File Format

Next-Gen Big Data File Format. Contribute to cwida/FastLanes development by creating an account on GitHub.

GitHub
Ah, yes, the riveting saga of cramming "user-defined indexes" into Apache Parquet files. 😴 Because who doesn’t love a story about exploiting footer metadata to do something nobody asked for? Next time, tell us how to alphabetize your sock drawer using ForestDB. 🧦📚
https://datafusion.apache.org/blog/2025/07/14/user-defined-parquet-indexes/ #userdefinedindexes #apacheparquet #footermetadata #techhumor #dataengineering #HackerNews #ngated
Embedding User-Defined Indexes in Apache Parquet Files - Apache DataFusion Blog

Embedding User-Defined Indexes in Apache Parquet Files - Apache DataFusion Blog

Apache Parquet users, take note: a CVSS 10.0 flaw in the Java module could let attackers run arbitrary code without any user action. Is your system protected? Discover the key steps to secure your data now.

https://thedefendopsdiaries.com/understanding-and-mitigating-the-apache-parquet-cve-2025-30065-vulnerability/

#apacheparquet
#cve202530065
#datasecurity
#cybersecurity
#vulnerability