Manage all types of time series data in a single, purpose-built database. Run at any scale in any environment in the cloud, on-premises, or at the edge. Learn more →
Weaviate Alternatives
Similar projects and alternatives to Weaviate
-
Milvus
A cloud-native vector database, storage for next generation AI applications
-
qdrant
Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
-
Onboard AI
Learn any GitHub repo in 59 seconds. Onboard AI learns any GitHub repo in minutes and lets you chat with it to locate functionality, understand different parts, and generate new code. Use it for free at www.getonboard.dev.
-
-
faiss
A library for efficient similarity search and clustering of dense vectors.
-
-
MeiliSearch
A lightning-fast search engine that fits effortlessly into your apps, websites, and workflow.
-
-
InfluxDB
Collect and Analyze Billions of Data Points in Real Time. Manage all types of time series data in a single, purpose-built database. Run at any scale in any environment in the cloud, on-premises, or at the edge.
-
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
-
-
-
manticoresearch
Easy to use open source fast database for search | Good alternative to Elasticsearch now | Drop-in replacement for E in the ELK soon
-
-
ann-benchmarks
Benchmarks of approximate nearest neighbor libraries in Python
-
ChatterBot
ChatterBot is a machine learning, conversational dialog engine for creating chat bots
-
sonic
🦔 Fast, lightweight & schema-less search backend. An alternative to Elasticsearch that runs on a few MBs of RAM.
-
-
awesome-vector-search
Collections of vector search related libraries, service and research papers
-
semantic-search-through-wikipedia-with-weaviate
Semantic search through a vectorized Wikipedia (SentenceBERT) with the Weaviate vector search engine
-
-
annoy
Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk
-
SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
Weaviate reviews and mentions
-
How to use Weaviate to store and query vector embeddings
In this tutorial, I introduce Weaviate, an open-source vector database, with the thenlper/gte-base embedding model from Alibaba, through Hugging Face's transformers library.
-
Choosing vector database: a side-by-side comparison
This will be solved in Weaviate https://github.com/weaviate/weaviate/issues/2424
-
Who's hiring developer advocates? (October 2023)
Link to GitHub -->
-
Do we think about vector dbs wrong?
Hey @rvrs, I work on Weaviate and we are doing some improvements around increasing write throughput:
1. gRPC. Using gRPC to write vectors has had a really nice performance boost. It is released in Weaviate core but here is still some work on do on the clients. Feel free to get in contact if you would like to try it out.
2. Parameter tuning. lowering `efConstruction` can speed up imports.
3. We are also working on async indexing https://github.com/weaviate/weaviate/issues/3463 which will further speed things up.
In comparison with pgvector, Weaviate has more flexible query options such as hybrid search and quantization to save memory on larger datasets.
-
Pros and cons of vector search in elastic?
Highly opinionated as I'm working for Weaviate, so take my comment with a large portion of salt.
My highly opinionated view is that for Elastic, they're not really open source and the dependency on Java of the Lucene ecosystem is a big disadvantage, so as you already said, speed, they're getting better at this, but if you need to scale, this problem scales with you.
So if you already have ELK stack and don't need to scale, sure go for it otherwise, Weaviate offers real open source, so use it for free on your own infrastructure https://github.com/weaviate/weaviate
-
Lost on LangChain: Can someone help with the Question Answer concept?
If you do not wish to store your private data on pinecone you can use open source alternatives like Weaviate where you can spin up your own instance. Other option could be to use Agents. You'll need to find sutaible agent for your database which will allow LLMs to directly query data from your private database.
-
Questions about memory, tree-of-thought, planning
I tried cromadb but had terrible performance and could not pin down the cause (likely a problem on my end). Weaviate was easy to setup and had excellent performance, this is probably what I will use in the future. Next on my list is txtinstruct, to finetune a model with data that does not change and using a vector db for everything else seems promising.
-
FANN: Vector Search in 200 Lines of Rust
Weaviate actually does use SIMD for AMD64 with Go assembly (cosine distance is just normalized dot product) https://github.com/weaviate/weaviate/blob/master/adapters/re...
-
Top 10 Best Vector Databases & Libraries
Weaviate (4.8k ⭐) → An open-source vector database that allows you to store data objects and vector embeddings from your favorite ML-models, and scale seamlessly into billions of data objects.
-
Vector Databases (power your embedding similarity search and AI applications).
weaviate
-
A note from our sponsor - InfluxDB
www.influxdata.com | 8 Dec 2023
Stats
weaviate/weaviate is an open source project licensed under BSD 3-clause "New" or "Revised" License which is an OSI approved license.
Weaviate is marked as "self-hosted". This means that it can be used as a standalone application on its own.
The primary programming language of Weaviate is Go.