Software Alternatives, Accelerators & Startups

Vectara Neural Search VS Haystack NLP Framework

Compare Vectara Neural Search VS Haystack NLP Framework and see what are their differences

Vectara Neural Search logo Vectara Neural Search

Neural search as a service API with breakthrough relevance

Haystack NLP Framework logo Haystack NLP Framework

Haystack is an open source NLP framework to build applications with Transformer models and LLMs.
  • Vectara Neural Search Landing page
    Landing page //
    2023-08-02
  • Haystack NLP Framework Landing page
    Landing page //
    2023-12-11

Category Popularity

0-100% (relative to Vectara Neural Search and Haystack NLP Framework)
Utilities
27 27%
73% 73
Search Engine
100 100%
0% 0
Communications
0 0%
100% 100
AI
34 34%
66% 66

User comments

Share your experience with using Vectara Neural Search and Haystack NLP Framework. For example, how are they different and which one is better?
Log in or Post with

Social recommendations and mentions

Based on our record, Vectara Neural Search should be more popular than Haystack NLP Framework. It has been mentiond 13 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Vectara Neural Search mentions (13)

  • Launch HN: Danswer (YC W24) – Open-source AI search and chat over private data
    Nice to see yet another open source approach to LLM/RAG. For those who do not want to meddle with the complexity of do-it-youself, Vectara (https://vectara.com) provides a RAG-as-a-service approach - pretty helpful if you want to stay away from having to worry about all the details, scalability, security, etc - and just focus on building your RAG application. - Source: Hacker News / 3 months ago
  • Which LLM framework(s) do you use in production and why?
    You should also check us out (https://vectara.com) - we provide RAG as a service so you don't have to do all the heavy lifting and putting together the pieces yourself. Source: 5 months ago
  • Show HN: Quepid now works with vetor search
    Hi HN! I lead product for Vectara (https://vectara.com) and we recently worked with OpenSource connections to both evaluate our new home-grown embedding model (Boomerang) as well as to help users start more quantitatively evaluating these systems on their own data/with their own queries. OSC maintains a fantastic open source tool, Quepid, and we worked with them to integrate Vectara (and to use it to... - Source: Hacker News / 7 months ago
  • A Comprehensive Guide for Building Rag-Based LLM Applications
    RAG is a very useful flow but I agree the complexity is often overwhelming, esp as you move from a toy example to a real production deployment. It's not just choosing a vector DB (last time I checked there were about 50), managing it, deciding on how to chunk data, etc. You also need to ensure your retrieval pipeline is accurate and fast, ensuring data is secure and private, and manage the whole thing as it... - Source: Hacker News / 8 months ago
  • Do we think about vector dbs wrong?
    I agree. My experience is that hybrid search does provide better results in many cases, and is honestly not as easy to implement as may seem at first. In general, getting search right can be complicated today and the common thinking of "hey I'm going to put up a vector DB and use that" is simplistic. Disclaimer: I'm with Vectara (https://vectara.com), we provide an end-to-end platform for building GenAI products. - Source: Hacker News / 8 months ago
View more

Haystack NLP Framework mentions (5)

  • Haystack DB – 10x faster than FAISS with binary embeddings by default
    I was confused for a bit but there is no relation to https://haystack.deepset.ai/. - Source: Hacker News / 16 days ago
  • Release Radar • March 2024 Edition
    People like to be on the AI bandwagon, but to have good AI models, you need good LLM (large language models). Welcome to Haystack, it's an end-to-end LLM framework that allows you to build applications powered by LLMs, Transformer models, vector search and more. The latest version is a rewrite of the Haystack framework, and includes a new package, powerful pipelines, customisable components, prompt templating, and... - Source: dev.to / about 1 month ago
  • Generative AI Frameworks and Tools Every Developer Should Know!
    Haystack can be classified as an end-to-end framework for building applications powered by various NLP technologies, including but not limited to generative AI. While it doesn't directly focus on building generative models from scratch, it provides a robust platform for:. - Source: dev.to / 5 months ago
  • Best way to programmatically extract data from a set of .pdf files?
    But if you want an API that you can use to develop your own flow, Haystack from Deepset could be worth a look. Source: 5 months ago
  • Which LLM framework(s) do you use in production and why?
    Haystack for production. We cannot afford breaking changes in our production apps. Its stable, documentation is excellent and did I mention its' STABLE!?? Source: 5 months ago

What are some alternatives?

When comparing Vectara Neural Search and Haystack NLP Framework, you can also consider the following products

txtai - AI-powered search engine

LangChain - Framework for building applications with LLMs through composability

Dify.AI - Open-source platform for LLMOps,Define your AI-native Apps

Hugging Face - The Tamagotchi powered by Artificial Intelligence 🤗

MiniGPT-4 - Minigpt-4

Annoy - Annoy is a C++ library with Python bindings to search for points in space that are close to a given query point.