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Products that do what dbzero does

Zero-latency persistence: Speed of RAM with safety of a DB.

  1. 1DC
  2. 2DT

    Hi HN - DBOS CEO here with the co-founders of DBOS, Peter (KraftyOne) and Qian (qianli_cs). The company started as a research project of Stanford and MIT, and Peter and Qian were advised by Mike Stonebreaker, the creator of Postgres, and Matei Zaharia, the creator of Spark. They believe so strongly in reliable, serverless compute that they started a company (with Mike) to bring it to the world! Today we want to share our brand new Python library providing ultra-lightweight durable execution. https://github.com/dbos-inc/dbos-transact-py Durable execution means your program…

    2024 · github.com

  3. 3IW

    I wrote a relational database management system (RDBMS) (sqlite clone) from scratch in pure Python.

    2023 · github.com

  4. 4SH

    At JigsawStack.com, we are using Redis by Upstash to store and validate API keys among other datasets for speedy retrieval. As we scaled to more Asian markets and added replicated nodes, the cost started to shoot up while performance got a lot worse. I discovered hosting SQLite on Fly which was crazy fast & cheap with the full power of a relational database but difficult to use and scale without writing tons of code & devops. Then I found Turso as a managed service which is pretty cool but again got really expensive and had to manage a bunch of replications manually and pay per replications…

    2024 · dzero.dev

  5. 5MG

    https://github.com/ncruces/go-sqlite3 was doing poorly on this benchmark that was posted yesterday to HackerNews [1]. With the help of some pprof, I was able to trace it to a serious performance regression introduced two weeks ago, and come up with the fix (happy to field questions, if you're interested in the nitty gritty). It's not the fastest driver around, but it's no longer the slowest: comfortably middle of the pack. It's based on a WASM build of SQLite, and thanks to https://wazero.io doesn't need CGO. [1]:…

    2023 · github.com

  6. 6MS

    My immediate reaction to today's news that Splunk was being acquired was to comment in the HN discussion for that story: "I hated Splunk so much that I spent a couple days a few months ago writing a single 1200 line python script that does absolutely everything I need in terms of automatic log collection, ingestion, and analysis from a fleet of cloud instances. It pulls in all the log lines, enriches them with useful metadata like the IP address of the instance, the machine name, the log source, the datetime, etc. and stores it all in SQlite, which it then exposes to a very convenient web…

    2023 · github.com

  7. 7AD

    Recently created a minimal persistent relational database in Go. Main focus was on implementing & understanding working the of database, storage management & transaction handling. Use of B+ Tree for storage engine(support for indexing), managing a Free List (for reusing nodes), Support for transactions, Concurrent Reads. Still have many things to add & fix like query processing being one of the main & fixing some bugs Repo link - https://github.com/Sahilb315/AtomixDB Would love to hear your thoughts

    2025 · github.com

  8. 8OP

    Hi HN! I built Oxyde because I was tired of duplicating my models. If you use FastAPI, you know the drill. You define Pydantic models for your API, then define separate ORM models for your database, then write converters between them. SQLModel tries to fix this but it's still SQLAlchemy underneath. Tortoise gives you a nice Django-style API but its own model system. Django ORM is great but welded to the framework. I wanted something simple: your Pydantic model IS your database model. One class, full validation on input and output, native type hints, zero duplication. The query API is…

    Mar 2026 · github.com

  9. 9TA

    As the creator of TerarkDB (acquired by ByteDance in 2019), I have developed ToplingDB in recent years. ToplingDB is forked from RocksDB, where we have replaced almost all components with more efficient alternatives(db_bench shows ToplingDB is about ~8x faster than RocksDB): * MemTable: SkipList is replaced by CSPP(Crash Safe Parallel Patricia trie), which is 8x faster. * SST: BlockBasedTable is replaced by ToplingZipTable, implemented by searchable compression algo, it is very small and fast, typically less than 1μs per lookup: * Keys/Indexes are compressed using NestLoudsTrie(a…

    2025 · github.com

  10. 10DJ

    Hi HN - I’m Peter, here with Harry (devhawk), and we’re building DBOS Java, an open-source Java library for durable workflows, backed by Postgres. https://github.com/dbos-inc/dbos-transact-java Essentially, DBOS helps you write long-lived, reliable code that can survive failures, restarts, and crashes without losing state or duplicating work. As your workflows run, it checkpoints each step they take in a Postgres database. When a process stops (fails, restarts, or crashes), your program can recover from those checkpoints to restore its exact state and continue from where…

    Nov 2025 · github.com

  11. 11PA
  12. 12DT

    Hi HN - Peter from DBOS here with my co-founder Qian (qianl_cs) Today we want to share our TypeScript library for lightweight durable execution. We’ve been working on it since last year and recently released v2.0 with a ton of new features and major API overhaul. https://github.com/dbos-inc/dbos-transact-ts Durable execution means persisting the execution state of your program while it runs, so if it is ever interrupted or crashes, it automatically resumes from where it left off. Durable execution is useful for a lot of things: - Orchestrating long-running or…

    2025 · github.com

  13. 13FB
  14. 14

    Postgres-Backed Drop-in Temporal Replacement. Contribute to dbos-inc/dbosify-py development by creating an account on GitHub.

    Jun 2026 · github.com

  15. 15SI

    2016 · github.com

  16. 16SB

    I had already posted the project a couple of years ago, and it gained some interest, but a lot of stuff has been done since then, especially regarding performance, a completely new JSON store, a REST API, various internals refactored, an improved JSONiq based query engine allowing updates, implementing set-oriented join optimizations, a now already dated web UI, a new Kotlin based CLI, a Python and TypeScript client to ease the use of Sirix... First prototypes from a precursor stem already from 2005. So, what is it all about? The system uses ideas from ZFS (a keyed index trie, storing…

    2023 · github.com

  17. 17GA

    I wanted to build a persistent message queue based on SQLite, because that's what I'm using for my main state anyway. This gives me ACID across state and messaging, which is nice! I've been inspired by the terminology of AWS SQS for this, but it's obviously much simpler. Maybe you can use it too. :)

    2024 · goqite.com

  18. 18DA
  19. 19DP

    Hi HN – this is Peter from DBOS here with Qian (qianli_cs) and Jeremy (jedberg). We’re building an open-source, lightweight durable workflows library on top of Postgres. Ever since we first launched on HN last year, we’ve been blown away by the support, feedback, and response we’ve received from the community. We've realized durable workflows are critical for everything from business processes to AI automation to data pipelines, but most existing durable orchestration tools are either too heavy or too complicated for most applications. Instead, we're building something lightweight, simple,…

    2025 · github.com

  20. 20LD

    Hi HN! This is Qian here with Peter (KraftyOne) and Jeremy (jedberg). We’re building DBOS, an open-source, lightweight durable workflows library that you can add to Python apps in just a few lines of code. It’s comparable to popular open-source workflow and queue libraries like Airflow and Celery, but more lightweight with a greater focus on reliability and automatically recovering from failures. Our goal in building DBOS is to make workflows lightweight and flexible so you can add them to your existing apps with minimal work. Everything you need to run durable workflows and queues is…

    2025 · github.com

  21. 21AB

    we've been working on a KV store for the past year or so which is 2-6x faster than Redis (benchmark link below) yet disk persisted! so you get the speed of in-memory KV stores but with disk persistence. To achieve this we've created our custom filesystem that is optimized for our special usecase and we're doing smart batching for writes and predictive fetching for reads. In addition to basic operations, it also provides atomic inc/dec, atomic json patch, range scans and a unique key monitoring mechanism (pub-sub) over WebSockets which essentially allows you to receive notification on…

    2025 · hpkv.io

  22. 22TA
  23. 23CA

    I built Copapy as an experiment: Can Python be used for hard real-time systems? Instead of an interpreter or JIT, Copapy builds a computation graph by tracing Python code and uses a custom copy-and-patch compiler. The result is very fast native code with no GC, no syscalls, and no memory allocations at runtime. The copy-and-patch compiler currently supports x86_64 as well as 32- and 64-bit ARM. It comes as small Python package with no other dependencies - no cross-compiler, nothing except Python. The current focus is on robotics and control systems in general. This project is early but…

    Feb 2026 · github.com

  24. 24AM

    Vector databases store memories. They don't manage them. After 10k memories, recall quality degrades because there's no consolidation, no forgetting, no conflict resolution. Your AI agent just gets noisier. YantrikDB is a cognitive memory engine — embed it, run it as a server, or connect via MCP. It thinks about what it stores: consolidation collapses duplicate memories, contradiction detection flags incompatible facts, temporal decay with configurable half-life lets unimportant memories fade like human memory does. Single Rust binary. HTTP + binary wire protocol. 2-voter + 1-witness HA…

    Apr 2026 · github.com

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