Penca – branchable, versioned OLTP+OLAP on one open copy of your data
Hi HN! This is an early proof of concept of a branchable, versioned OLTP + OLAP database that runs on a single, open copy of your data in object storage. If you are familiar with Databricks' LTAP (https://www.databricks.com/company/newsroom/press-releases/d...) announcement from June, you can think of this as aspiring to be a fully open source, Apache 2.0 LTAP alternative with additional data versioning/auditability guarantees that enable audit, as_of queries, and (eventually) revert straight out of the box. How it works: 1. Writes land in vanilla postgres…
In plain words
Penca is an open-source database that combines transactional and analytical capabilities on a single copy of data stored in object storage. It uses PostgreSQL for writes, automatically flushes committed data to columnar files, and queries both layers using a DataFusion-based engine. The system includes built-in data versioning and auditability features, enabling audit trails, point-in-time queries, and data recovery. It is designed for developers and organizations seeking an open alternative to commercial LTAP solutions.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Hi HN! This is an early proof of concept of a branchable, versioned OLTP + OLAP database that runs on a single, open copy of your data in object storage. If you are familiar with Databricks' LTAP (https://www.databricks.com/company/newsroom/press-releases/d...) announcement from June, you can think of this as aspiring to be a fully open source, Apache 2.0 LTAP alternative with additional data versioning/auditability guarantees that enable audit, as_of queries, and (eventually) revert straight out of the box. How it works: 1. Writes land in vanilla postgres which functions as an ephemeral hot tier 2. A background pass flushes committed rows out to columnar files in an object storage cold tier 3. A DataFusion based query engine merges results across the two tiers (with some fancy caching and indexing) For a deep dive on the architecture/intended design/vision see: https://penca.io/blog/the-penca-architecture.html. This project is very, very early on. It is mostly a PoC right now and there are many bugs and shortcomings with many major items still on the roadmap. I hope to get some real performance numbers soon. A few features I would like to add in no particular order: - Iceberg export - Branching (from any branch, not just main) - Improved SQL support (e.g. multi-statement execution) - Full-text search and vector indexes - Configurable isolation levels (currently last write wins) - A pgwire frontend Any and all feedback is appreciated. I'd also like help! If any of this appeals to you and the project doesn't seem like the craziest idea of all time, shoot me an email at [email protected]. Disclaimer: before someone comments this, yes, the code is heavily AI generated. I have tried to leave as much of the dev tooling in the repo as possible to demonstrate what the end-to-end development workflow looks like. Also, the majority of the commit history is missing as I had to rename/migrate + scrub the repo prior to open sourcing.
Does the same job
all alternatives →- BPBemiDB – Postgres read replica optimized for analytics2024 · github.com · ▲209
Hi HN! We're Evgeny and Arjun, and we’re building a better way to do analytics with Postgres. We love Postgres for its simplicity, power, and rich ecosystem. But engineers have to still get bogged down with heavyweight and expensive OLAP systems when connecting an analytics data stack. Postgres is amazing at OLTP queries, but not for OLAP queries (large data scans and aggregations). Even in this case, we’ve still heard from countless scaling startups that they still try to use only a read replica to run analytics workloads since they don’t want to deal with the data engineering complexity of…
- OOOmni – Open-source workplace search and chat, built on PostgresMar 2026 · github.com · ▲177
Hey HN! Over the past few months, I've been working on building Omni - a workplace search and chat platform that connects to apps like Google Drive/Gmail, Slack, Confluence, etc. Essentially an open-source alternative to Glean, fully self-hosted. I noticed that some orgs find Glean to be expensive and not very extensible. I wanted to build something that small to mid-size teams could run themselves, so I decided to build it all on Postgres (ParadeDB to be precise) and pgvector. No Elasticsearch, or dedicated vector databases. I figured Postgres is more than capable of handling the level…
- HAHelixDB – A graph database built on object storageJun 2026 · github.com · ▲159
Hey HN, it’s been just over a year since we launched HelixDB (https://news.ycombinator.com/item?id=43975423), a project a friend and I started in college. It’s an OLTP graph database built on object-storage, with native vector search and full-text search (FTS). Why graph, vector and FTS? Graph databases provide a natural cognitive model for data, vectors allow for a semantic understanding of the entities and relationships in the graph, and FTS provides more specific filtering. Many AI-driven applications attempt to combine all of these functionalities by stitching together…
- VSVelvet – Store OpenAI requests in your own DB2024 · usevelvet.com · ▲109
Hey HN! We’re Emma and Chris, founders of Velvet (https://www.usevelvet.com). Velvet proxies OpenAI calls and stores the requests and responses in your PostgreSQL database. That way, you can analyze logs with SQL (instead of a clunky UI). You can also set headers to add caching and metadata (for analysis). Backstory: We started by building some more general AI data tools (like a text-to-SQL editor). We were frustrated by the lack of basic LLM infrastructure, so ended up pivoting to focus on the tooling we wanted. So many existing apps, like Helicone, were hard to use as power…
- OOOLake[open source] Fastest database to Iceberg data replication tool2025 · ▲14
Hi HN, Today we’re excited to introduce OLake (github.com/datazip-inc/olake, 130+ and growing fast), an open-source tool built to help you replicate Database (MongoDB, for now, mysql and postgres under development) data into Data Lakehouse at faster speed without any hassle of managing Debezium or kafka (at least 10x faster than Airbyte and Fivetran at fraction of the cost, refer docs for benchmarks - https://olake.io/docs/connectors/mongodb/benchmarks). You might think “we don't need yet another ETL tool”, true but we tried existing tools (proprietary…
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I might be the only SRE on Earth with his own bowling center. It's a more in-depth gig than you'd think. My family and I bought an abandoned 8-lane bowling center in the rural mid-west. In our small town there weren't many recreation options for families. You've heard of a food desert? This is an R&R desert. It had been abandoned for a good reason. The roof leaks, the electrical system was constantly surging, and my 70-year-old bowling equipment (still) doesn't work perfectly. The system that keeps your score is particularly interesting to me. It's the thing you watch during your game, but…
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Over the past few months, our team has been building more and more slidedecks using web frontend technologies with coding harnesses like Claude Code, but a common complaint is to make even small edits we need to edit the code either manually or via the harness. To avoid this loop, I ended up creating Bento, a single HTML file with everything you need in a slide tool including animations and shared editing. There's no install or cloud login, everything works offline. The default deck is around 560 KB and it doesn't need to fetch anything once you got it. Open it in a browser and then you can…
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A few days ago I found myself trying out GLM 5.2 and was really positively impressed. The capabilities and security I was getting from this LLM are similar to those I've gotten from models like Claude or GPT, and this really surprised me. But then I thought, "I wonder how it would work on a normal computer like mine," and above all, "I wonder if it would work without going into OOM on a computer like mine." So I started working with the help of agents to test this possibility. I started converting the model to int4, understanding MTP usage, and if possible implementing DSA for long context.…
AI · Jul 2026 · github.com
