vespa
milvus-lite
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| vespa | milvus-lite | |
|---|---|---|
| 4 | 4 | |
| 5,336 | 146 | |
| 2.5% | 9.6% | |
| 10.0 | 5.7 | |
| 6 days ago | 20 days ago | |
| Java | Python | |
| Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
vespa
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Top 10 Best Vector Databases & Libraries
Vespa(4.3k ⭐) → A fully featured search engine and vector database. It supports vector search (ANN), lexical search, and search in structured data, all in the same query. Integrated machine-learned model inference allows you to apply AI to make sense of your data in real time.
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Vector database built for scalable similarity search
If ES doesn't work for you, I recommend Vespa. https://github.com/vespa-engine/vespa
Others have made other suggestions, but Vespa has two unique features. First it is battle tested at a large scale, second it supports combining the keyword and vector scores in several ways. The latter is something that other hybrid systems don't do very well in my experience including ES/Solr.
- ZincSearch – lightweight alternative to Elasticsearch written in Go
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MeiliSearch: A Minimalist Full-Text Search Engine
After looking at various alternatives, I'm thinking of trying out https://vespa.ai/ [0]
[0] https://github.com/vespa-engine/vespa
milvus-lite
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Simplifying the Milvus Selection Process
Github Repository
- FLaNK Stack Weekly 16 October 2023
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Vector databases: analyzing the trade-offs
Shameless self-plug for our embedded vector database milvus-lite (https://github.com/milvus-io/milvus-lite):
pip install milvus -
Vector database built for scalable similarity search
Don't start with Milvus clustered version, not unless you have like 100million vectors.
Try Milvus standalone instead, much simpler. I also just found their python version (https://github.com/milvus-io/embd-milvus), which is quite neat.
What are some alternatives?
Typesense - Open Source alternative to Algolia + Pinecone and an Easier-to-Use alternative to ElasticSearch ⚡ 🔍 ✨ Fast, typo tolerant, in-memory fuzzy Search Engine for building delightful search experiences
examples - Analyze the unstructured data with Towhee, such as reverse image search, reverse video search, audio classification, question and answer systems, molecular search, etc.
qdrant - Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
sqlite-vss - A SQLite extension for efficient vector search, based on Faiss!
pgvector - Open-source vector similarity search for Postgres
kafka-ui - Open-Source Web UI for Apache Kafka Management
Infinispan - Infinispan is an open source data grid platform and highly scalable NoSQL cloud data store.
karapace - Karapace - Your Apache Kafka® essentials in one tool
milli - Search engine library for Meilisearch ⚡️
CML_AMP_AI_Text_Summarization_with_Amazon_Bedrock - CML_AMP_AI_Text_Summarization_with_Amazon_Bedrock
pgroonga - PGroonga is a PostgreSQL extension to use Groonga as index. PGroonga makes PostgreSQL fast full text search platform for all languages!
autofaiss - Automatically create Faiss knn indices with the most optimal similarity search parameters.