Alternatives
Products that do what YugabyteDB 2025.2 does
Ultra-resilient scalable distributed PostgreSQL AI database
- 1LA
We are excited to share Lantern! Lantern is a PostgreSQL vector database extension for building AI applications. Install and use our extension here: https://github.com/lanterndata/lantern We have the most complete feature set of all the PostgreSQL vector database extensions. Our database is built on top of usearch — a state of the art implementation of HNSW, the most scalable and performant algorithm for handling vector search. There’s three key metrics we track. CREATE INDEX time, SELECT throughput, and SELECT latency. We match or outperform pgvector and pg_embedding…
2023 · docs.lantern.dev
- 2CH
Hi HN! We're thrilled to share CozoDB v0.6, a monumental update to our FOSS database, which already unifies relational and graph features. With the addition of vector search, CozoDB becomes an even better companion for LLMs like ChatGPT. This release introduces vector search using HNSW indices within Datalog, enabling seamless integration with powerful features such as ad-hoc joins, recursive Datalog, and classical whole-graph algorithms. This update significantly broadens CozoDB's capabilities. Check out the linked release note for an in-depth look at the new features, comparisons to other…
2023 · docs.cozodb.org
- 3SU
2014 · github.com
- 4PA
2024 · github.com
- 5
- 6GF
2015 · github.com
- 7BA
2016 · bedquiltdb.github.io
- 8HO
Hey HN, we want to share HelixDB (https://github.com/HelixDB/helix-db/), a project a college friend and I are working on. It’s a new database that natively intertwines graph and vector types, without sacrificing performance. It’s written in Rust and our initial focus is on supporting RAG. Here’s a video runthrough: https://screen.studio/share/szgQu3yq. Why a hybrid? Vector databases are useful for similarity queries, while graph databases are useful for relationship queries. Each stores data in a way that’s best for its main type of query (e.g.…
2025 · github.com
- 9
The portable vector database for AI agents beyond the cloud
Apr 2026 · actian.com
- 10TS
2016 · torodb.com
- 11GI
2016 · github.com
- 12DL
2014 · databaselabs.io
- 13
- 14EO
Hey HN! We are building Epsilla (https://github.com/epsilla-cloud/vectordb), an open-source, self-hostable vector database for semantic similarity search that specializes in low query latency. When do we need a vector database? For example, GPT-3.5 has a 16k context window limit. If we want to let it answer a question about a 300 page book, we cannot put the whole book content into the context. We have to choose the sections of the book that are most relevant to the question. Vector database is specialized at ranking and picking the most relevant content from a large pool…
2023 · github.com
- 15AF
2024 · github.com
- 16AE
2019 · github.com
- 17IB
2024 · github.com
- 18DA
2018 · github.com
- 19PA
2014 · phoenix.incubator.apache.org
- 20RA
2017 · github.com
- 21PC
2016 · github.com
- 22
Hi HN - I'm Venkat, founder of Stayflexi (YC), CMU CS grad and Ex-Oracle Query Engine team (patents in core databases) DeepSQL started as an internal tool to stop our own databases from becoming the bottleneck they were becoming (13,000+ hotels in production). It worked well enough that we're releasing it. DeepSQL is an AI agent that operates a database the way a senior DBA and Data Engineer would 1. Fixes slow queries (we cutdown DB spend by 4x) 2. Fixes DB bloat (blocks unnecessary schema changes, in vibecoded setup) 2. BI dashboards(we removed spend on tableau, retool and appsmith) 3.…
Jul 2026 · deepsql.ai
- 23
- 24MO
2024 · github.com
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