AthenaDB vs Milvus
Overview
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CLI (Node.js)
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Detailed Comparison
Milvus is an open source vector database. Built with heterogeneous computing architecture for the best cost efficiency. Searches over billion-scale vectors take only milliseconds with minimum computing resources. | It is a simple, serverless, distributed vector database that can be used as an API. It is designed to handle large amounts of vector text data, making it suitable for projects with high data volumes. |
Heterogeneous computing; Multiple indexes; Intelligent resource management; Horizontal scalability; High availability | Simple API endpoints;
Distributed nature;
Built-in data replication;
Serverless architecture |
Statistics | |
GitHub Stars 38.3K | GitHub Stars 270 |
GitHub Forks 3.5K | GitHub Forks 8 |
Stacks 62 | Stacks 0 |
Followers 49 | Followers 1 |
Votes 2 | Votes 0 |
Pros & Cons | |
Pros
| No community feedback yet |
Integrations | |
What are some alternatives to Milvus, AthenaDB?
Qdrant
It is an open-source Vector Search Engine and Vector Database written in Rust. It deploys as an API service providing search for the nearest high-dimensional vectors. With Qdrant, embeddings or neural network encoders can be turned into full-fledged applications for matching, searching, recommending, and much more.
Chroma
It is an open-source embedding database. Chroma makes it easy to build LLM apps by making knowledge, facts, and skills pluggable for LLMs.
LanceDB
It is an open-source database for vector search built with persistent storage, which greatly simplifies retrieval, filtering, and management of embeddings.
Lantern
It is an open-source PostgreSQL database extension to store vector data, generate embeddings, and handle vector search operations. It provides a new index type for vector columns which speeds up ORDER BY ... LIMIT queries.
Pg_vectorize
It is a Postgres extension that automates the transformation and orchestration of text to embeddings and provides hooks into the most popular LLMs. This allows you to do vector search and build LLM applications on existing data with as little as two function calls.
Epsilla
It is an open-source, self-hostable vector database for semantic similarity search that specializes in low query latency. It bridges the gap between information retrieval and memory retention in Large Language Models.
