ann-benchmarks VS txtai

Compare ann-benchmarks vs txtai and see what are their differences.

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ann-benchmarks txtai
51 360
4,748 7,516
- 3.8%
7.5 9.3
27 days ago 1 day ago
Python Python
MIT License Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

ann-benchmarks

Posts with mentions or reviews of ann-benchmarks. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-10-30.
  • Using Your Vector Database as a JSON (Or Relational) Datastore
    1 project | news.ycombinator.com | 23 Apr 2024
    On top of my head, pgvector only supports 2 indexes, those are running in memory only. They don't support GPU indexing, nor Disk based indexing, they also don't have separation of query and insertions.

    Also with different people I've talked to, they struggle with scale past 100K-1M vector.

    You can also have a look yourself from a performance perspective: https://ann-benchmarks.com/

  • ANN Benchmarks
    1 project | news.ycombinator.com | 25 Jan 2024
  • Approximate Nearest Neighbors Oh Yeah
    5 projects | news.ycombinator.com | 30 Oct 2023
    https://ann-benchmarks.com/ is a good resource covering those libraries and much more.
  • pgvector vs Pinecone: cost and performance
    1 project | dev.to | 23 Oct 2023
    We utilized the ANN Benchmarks methodology, a standard for benchmarking vector databases. Our tests used the dbpedia dataset of 1,000,000 OpenAI embeddings (1536 dimensions) and inner product distance metric for both Pinecone and pgvector.
  • Vector database is not a separate database category
    3 projects | news.ycombinator.com | 2 Oct 2023
    Data warehouses are columnar stores. They are very different from row-oriented databases - like Postgres, MySQL. Operations on columns - e.g., aggregations (mean of a column) are very efficient.

    Most vector databases use one of a few different vector indexing libraries - FAISS, hnswlib, and scann (google only) are popular. The newer vector dbs, like weaviate, have introduced their own indexes, but i haven't seen any performance difference -

    Reference: https://ann-benchmarks.com/

  • How We Made PostgreSQL a Better Vector Database
    2 projects | news.ycombinator.com | 25 Sep 2023
    (Blog author here). Thanks for the question. In this case the index for both DiskANN and pgvector HNSW is small enough to fit in memory on the machine (8GB RAM), so there's no need to touch the SSD. We plan to test on a config where the index size is larger than memory (we couldn't this time due to limitations in ANN benchmarks [0], the tool we use).

    To your question about RAM usage, we provide a graph of index size. When enabling PQ, our new index is 10x smaller than pgvector HNSW. We don't have numbers for HNSWPQ in FAISS yet.

    [0]: https://github.com/erikbern/ann-benchmarks/

  • Do we think about vector dbs wrong?
    7 projects | news.ycombinator.com | 5 Sep 2023
  • Vector Search with OpenAI Embeddings: Lucene Is All You Need
    2 projects | news.ycombinator.com | 3 Sep 2023
    In terms of "All You Need" for Vector Search, ANN Benchmarks (https://ann-benchmarks.com/) is a good site to review when deciding what you need. As with anything complex, there often isn't a universal solution.

    txtai (https://github.com/neuml/txtai) can build indexes with Faiss, Hnswlib and Annoy. All 3 libraries have been around at least 4 years and are mature. txtai also supports storing metadata in SQLite, DuckDB and the next release will support any JSON-capable database supported by SQLAlchemy (Postgres, MariaDB/MySQL, etc).

  • Vector databases: analyzing the trade-offs
    5 projects | news.ycombinator.com | 20 Aug 2023
    pg_vector doesn't perform well compared to other methods, at least according to ANN-Benchmarks (https://ann-benchmarks.com/).

    txtai is more than just a vector database. It also has a built-in graph component for topic modeling that utilizes the vector index to autogenerate relationships. It can store metadata in SQLite/DuckDB with support for other databases coming. It has support for running LLM prompts right with the data, similar to a stored procedure, through workflows. And it has built-in support for vectorizing data into vectors.

    For vector databases that simply store vectors, I agree that it's nothing more than just a different index type.

  • Vector Dataset benchmark with 1536/768 dim data
    3 projects | news.ycombinator.com | 14 Aug 2023
    The reason https://ann-benchmarks.com is so good, is that we can see a plot of recall vs latency. I can see you have some latency numbers in the leaderboard at the bottom, but it's very difficult to make a decision.

    As a practitioner that works with vector databases every day, just latency is meaningless to me, because I need to know if it's fast AND accurate, and what the tradeoff is! You can't have it both ways. So it would be helpful if you showed plots showing this tradeoff, similar to ann-benchmarks.

txtai

Posts with mentions or reviews of txtai. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-06-29.
  • txtai: Vector search, Knowledge Graphs, RAG and LLM workflows locally run
    2 projects | news.ycombinator.com | 29 Jun 2024
    Hello, author of txtai here. txtai was created back in 2020 starting with semantic search of medical literature. It has since grown into a framework for vector search, retrieval augmented generation (RAG) and large language model (LLM) orchestration.

    The goal of txtai is to be simple and easy-to-use. Semantic Graphs were added in 2022 before the Generative AI wave of 2023/2024. Knowledge Graphs are now a hot topic, so this component is even more relevant today. txtai also has a robust RAG and workflow framework.

    I often see others complain about AI/LLM/RAG frameworks, so I wanted to share this project as many don't know it exists.

    txtai is Apache 2.0 licensed and all code is available at https://github.com/neuml/txtai

  • How RAG with txtai works
    1 project | dev.to | 21 Jun 2024
    # Set base image ARG BASE_IMAGE=neuml/txtai-gpu FROM $BASE_IMAGE # Copy configuration COPY config.yml . # Install latest version of txtai from GitHub RUN \ apt-get update && \ apt-get -y --no-install-recommends install git && \ rm -rf /var/lib/apt/lists && \ python -m pip install git+https://github.com/neuml/txtai # Run local API instance to cache models in container RUN python -c "from txtai.api import API; API('config.yml')" # Start server and listen on all interfaces ENV CONFIG "config.yml" ENTRYPOINT ["uvicorn", "--host", "0.0.0.0", "txtai.api:app"]
  • We no longer use LangChain for building our AI agents
    10 projects | news.ycombinator.com | 20 Jun 2024
    An alternative is using txtai (https://github.com/neuml/txtai). It's lightweight and works with both local and remote LLMs.

    Here is an example article that shows how to use OpenAI calls with txtai: https://neuml.hashnode.dev/rag-with-llamacpp-and-external-ap...

  • Show HN: FileKitty – Combine and label text files for LLM prompt contexts
    5 projects | news.ycombinator.com | 1 May 2024
  • What contributing to Open-source is, and what it isn't
    1 project | news.ycombinator.com | 27 Apr 2024
    I tend to agree with this sentiment. Many junior devs and/or those in college want to contribute. Then they feel entitled to merge a PR that they worked hard on often without guidance. I'm all for working with people but projects have standards and not all ideas make sense. In many cases, especially with commercial open source, the project is the base of a companies identity. So it's not just for drive-by ideas to pad a resume or finish a school project.

    For those who do want to do this, I'd recommend writing an issue and/or reaching out to the developers to engage in a dialogue. This takes work but it will increase the likelihood of a PR being merged.

    Disclaimer: I'm the primary developer of txtai (https://github.com/neuml/txtai), an open-source vector database + RAG framework

  • Build knowledge graphs with LLM-driven entity extraction
    1 project | dev.to | 21 Feb 2024
    txtai is an all-in-one embeddings database for semantic search, LLM orchestration and language model workflows.
  • Bootstrap or VC?
    1 project | news.ycombinator.com | 5 Feb 2024
    Bootstrapping only works if you have the runway to do it and you don't feel the need to grow fast.

    With NeuML (https://neuml.com), I've went the bootstrapping route. I've been able to build a fairly successful open source project (txtai 6K stars https://github.com/neuml/txtai) and a revenue positive company. It's a "live within your means" strategy.

    VC funding can have a snowball effect where you need more and more. Then you're in the loop of needing funding rounds to survive. The hope is someday you're acquired or start turning a profit.

    I would say both have their pros and cons. Not all ideas have the luxury of time.

  • txtai: An embeddings database for semantic search, graph networks and RAG
    1 project | news.ycombinator.com | 3 Feb 2024
  • Ask HN: What happened to startups, why is everything so polished?
    2 projects | news.ycombinator.com | 27 Jan 2024
    I agree that in many cases people are puffing their feathers to try to be something they're not (at least not yet). Some believe in the fake it until you make it mentality.

    With NeuML (https://neuml.com), the website is a simple HTML page. On social media, I'm honest about what NeuML is, that I'm in my 40s with a family and not striving to be the next Steve Jobs. I've been able to build a fairly successful open source project (txtai 6K stars https://github.com/neuml/txtai) and a revenue positive company. For me, authenticity and being genuine is most important. I would say that being genuine has been way more of an asset than liability.

  • Are we at peak vector database?
    8 projects | news.ycombinator.com | 25 Jan 2024
    I'll add txtai (https://github.com/neuml/txtai) to the list.

    There is still plenty of room for innovation in this space. Just need to focus on the right projects that are innovating and not the ones (re)working on problems solved in 2020/2021.

What are some alternatives?

When comparing ann-benchmarks and txtai you can also consider the following projects:

pgvector - Open-source vector similarity search for Postgres

sentence-transformers - Multilingual Sentence & Image Embeddings with BERT

faiss - A library for efficient similarity search and clustering of dense vectors.

tika-python - Tika-Python is a Python binding to the Apache Tika™ REST services allowing Tika to be called natively in the Python community.

Milvus - A cloud-native vector database, storage for next generation AI applications

tlsh

transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

pgANN - Fast Approximate Nearest Neighbor (ANN) searches with a PostgreSQL database.

CLIP - CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

vald - Vald. A Highly Scalable Distributed Vector Search Engine

paperai - 📄 🤖 Semantic search and workflows for medical/scientific papers

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