Alternatives
Products that do what Slater does
Low-RAM fast graph DB designed for local replica graphs.
- 1HA
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…
Jun 2026 · github.com
- 2TA
2020 · terminusdb.com
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I've been working on Polign and built a small prototype around something I've been thinking about with agent memory. I have built a lightweight/stateless vector db + BM25 search which works really well with typed facts and structured queries. It uses your own S3, or GCS bucket as primary storage, and restarting a node is fairly quick. Demo + writeup: https://polign.com/blog-edge-agent-memory Live search demo: https://demo.polign.com Docs: https://polign.com
11d ago · polign.com
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File-based memory for OpenClaw with >92% retrieval accuracy
Mar 2026
- 8GA
Hi HN, I have been working with regulation-heavy documents lately, and one thing kept bothering me. Flat RAG pipelines often fail to retrieve related articles together, even when they are clearly connected through references, definitions, or clauses. After trying several RAG setups, I subjectively felt that GraphRAG was a better mental model for this kind of data. The Microsoft GraphRAG paper and reference implementation were helpful starting points. However, in practice, I found one recurring friction point: graph storage and vector indexing are usually handled by separate systems, which…
Jan 2026 · github.com
- 98R
2019 · 8base.com
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2020 · github.com
- 12MT
2020 · memgraph.com
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Hi HN, I am one of the cofounders of http://turingdb.ai. We built TuringDB while working on large biological knowledge graphs and graph-based digital twins with pharma & hospitals, where existing graph databases were unusable for deep graph traversals with hundreds or thousands of hops on (crappy) machines you can find in a hospital. https://github.com/turing-db/turingdb TuringDB is a new in-memory, column-oriented graph database optimised for read-heavy analytical workloads: - Milliseconds (1) for multi-hop queries on graphs with 10M+ nodes/edges -…
Jan 2026 · github.com
- 14GB
2015 · github.com
- 15DG
2016 · github.com
- 16IW
Input a SMILES string (or pick one molecule from the examples) and it returns up to 100k molecules closest in 3-D shape or electrostatic similarity – from 10+ billion scale databases — typically in under 5-10 s. *Why it might interest HN* * Entire index lives on disk — no GPU at query-time, less than ~10 GB RAM total. * Built from scratch (no FAISS index / Milvus / Pinecone). * Index-build cost: one Nvidia T4 (~ 300USD) for one 5.5B database. * Open to anyone, predict ADMET, export results as CSV/SDF. Full write-up & benchmarks (DUD-E, LIT-PCBA, SVS) in the pre-print:…
2025 · cheese-new.deepmedchem.com
- 17OA
Hi HN, we're Kiran and Vijay! Over the past two years, we have built a columnar storage engine for observability: logs, metrics, and traces. Today, it's exciting for us to show what we've built on top of that foundation: LLM Agent Observability. Given how non-deterministic agents are, storing all traces without sampling was critical for us. But these traces tend to be in the MBs, sometimes GBs - we needed to store them inexpensively. We also needed the queries and analyses to be fast. To meet both these goals, we store them in S3 in our own parquet-like file format, and query them using AWS…
Jul 2026 · oodle.ai
- 18FO
Hey HN, I’m Roi, one of the co-creators of FalkorDB. We’re a growing team working on a graph database designed for production workloads and GraphRAG systems. The new release (v4.10.0) is out, and I wanted to share some of the updates and ask for feedback from folks who care about performance, memory efficiency in graph-heavy systems. FalkorDB is an open-source property graph database that supports OpenCypher (with our own extensions) and is used under the hood for retrieval-augmented generation setups where accuracy matters. The big problem we’re working on is scaling graph databases without…
2025
- 19RR
2019 · rxdb.info
- 20GQ
2017 · github.com
- 21SD
2020 · splitgraph.com
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I wanted to know how fast a 26B mixture-of-experts model could run on a desktop CPU with no GPU. Got ~40 tok/s single-stream (lossless) and ~124 batched. The surprising part was the byte budget: for this model you compress the output head (32% of per-token bytes), not the experts (16%). The writeup has the bandwidth roofline and the dead-ends; the repo has the reproducible recipe. Happy to answer questions. Repo: https://github.com/arun-prasath2005/gemma4-cpu-moe
Jun 2026 · apeg.dev
- 23BA
If we want better web3 experiences, developers need better tools. RPC nodes are really good at executing transactions, however they are notoriously cumbersome to set up, and reading large chunks of data is not very efficient: To show a list of transactions and receipts, nodes have to re-execute smart contract code on entire blocks. For every read call. Not great at scale. Which is why everyone is building ETLs to move data from the chain into their own database. This GraphQL API is our first step in allowing developers to spend more time on building product, rather than ETL infrastructure.
2022 · basement.dev
- 24GA
Hi, Hacker News! We're excited to announce the release of GraphAr, an open-source file format for archiving and exchanging graph data. The landscape of graph processing systems is fragmented, with various types of systems, including graph databases, graph computation systems, and GNN systems. However, currently, there is no common file format for efficiently storing and exchanging graph data while maintaining its schema and graph semantics. GraphAr is designed to address this issue by providing a simple, lightweight format for storing and exchanging graph data. GraphAr is a flexible and…
2023 · github.com
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