Stars and mentions
Last 30 days, Oct 5 – Nov 3
Package downloads
Top repositories
prestodb’s repositories ranked by new stars, as on trending.
Contributes to
Repositories outside prestodb’s account where prestodb opened or reviewed pull requests in the past 365 days.
Who noticed prestodb
Everyone who starred or forked prestodb’s repositories since the archive began in 2011.
Notable accounts
Ordered by the stars their own repositories have received.
Biggest fans
Accounts that starred the most of these repositories.
Breakout weeks
Each repository’s best week of new stars, with the release published around it.
- Gold
- 21st place finishes
- Silver
- 42nd place finishes
- Bronze
- 13rd place finishes
- Awarded repositories
- 1Owned by prestodb now
Repositories
Ordered by gold, then silver, then bronze.
- prestoBest: 1st by stars, 753 stars241
Every award
Top-three finishes of these repositories in completed trending days and weeks, newest first.
- #2 by forksDaily trending
42 forksas facebook/prestopresto - #3 by starsDaily trending
241 starsas facebook/prestopresto - #1 by starsDaily trending
753 starsas facebook/prestopresto - #1 by forksDaily trending
145 forksas facebook/prestopresto - #2 by starsDaily trending
302 starsas facebook/prestopresto - #2 by starsWeek of
1,452 starsas facebook/prestopresto - #2 by forksWeek of
233 forksas facebook/prestopresto
A repository earns an award for finishing first, second or third in a completed trending day or week, ranked by new stars, new forks or pull request authors. Awards follow a repository through renames and transfers and count toward its current owner. Weeks run Monday to Sunday, UTC.
Mentions
From Ingestion to Insights: Building a Data Lakehouse Pipeline for GitHub Analytics (Hands-On) 🚀 In this hands-on workshop, we build a complete, production-grade Data Lakehouse running 100% locally in Docker. Learn how to ingest the real-time public GitHub Archive firehose (1.78M+ events) into transactional Apache Hudi tables on S3/MinIO, catalog them with the Apache Hive Metastore, run distributed SQL analytics with PrestoDB, enforce data-quality gates with Apache Airflow, and visualize insights in Apache Superset, with ZERO ETL data replication. 👉 Register for the workshop: prestodb.io 💻 GitHub Repository & Code: saurabhmahawar/presto_hudi_github_data_pipeline ⭐ Don't forget to STAR the repository if you find it helpful. 📅 DATE: October 15, 2026 ⏰ TIME: 9:00 PM IST | 8:30 AM PDT 📌 WHAT YOU'LL LEARN: ✅ PrestoDB Hudi Connector: How distributed PrestoDB (1 Coordinator + 2 Workers) reads Copy-on-Write (COW) Parquet files on S3/MinIO with zero merge overhead. ✅ Schema Evolution & Nested Queries: Using Presto's native SQL dot-notation to query deeply nested, polymorphic structs. ✅ Presto as a Quality Gate: Connecting via PyHive DB-API inside Airflow to run 5 automated SQL assertions (deduplication invariants, volume, freshness) before promoting batches. ✅ Hudi ACID Superpowers: Witnessing in-place record mutations, GDPR point deletes ("Right to be Forgotten"), and timeline rollbacks. ✅ Zero-ETL BI Analytics: Querying Presto live from Apache Superset to power interactive dashboards across 1.78M records without data copies. --------------------------------------------------------------------------------------------------------------------------- 🔗 OFFICIAL LINKS & RESOURCES: • Workshop Registration: prestodb.io • Presto Official Website: prestodb.io • Presto Documentation (Hudi Connector): prestodb.io • Presto Slack Community: join.slack.com • Presto GitHub: prestodb/presto --------------------------------------------------------------------------------------------------------------------------- 🤝 Already using Presto? We’d love to hear about your experience — share your use case with us: forms.cloud.microsoft --------------------------------------------------------------------------------------------------------------------------- 🔔 Subscribe to the channel & turn on notifications for future workshop announcements #PrestoDB #ApacheHudi #DataLakehouse #DataEngineering #ApacheSpark #ApacheAirflow #Docker #ApacheSuperset #SQL #BigData