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Vespa.ai VS Sphinx Search

Compare Vespa.ai VS Sphinx Search and see what are their differences

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Vespa.ai logo Vespa.ai

Store, search, rank and organize big data

Sphinx Search logo Sphinx Search

Sphinx is an open source full text search server, designed with performance, relevance (search quality), and integration simplicity in mind. Sphinx lets you either batch index and search data stored in files, an SQL database, NoSQL storage.
  • Vespa.ai Landing page
    Landing page //
    2023-05-13
  • Sphinx Search Landing page
    Landing page //
    2021-10-08

Vespa.ai features and specs

  • Scalability
    Vespa.ai can handle large-scale data processing and real-time analytics, making it suitable for enterprises with vast data sets and high performance requirements.
  • Flexibility
    Offers the ability to deploy applications on various infrastructures whether on-premises, in the cloud, or in hybrid environments, which enhances deployment flexibility.
  • Real-time Data Processing
    Designed to facilitate real-time data ingestion and querying, which supports applications that require fast data retrieval and processing.
  • Open Source
    Being open-source allows developers to customize and contribute to the platform, fostering community engagement and innovation.
  • Advanced Search Capabilities
    Provides a strong search engine that supports natural language processing and complex query handling, which enhances user interactions and data retrieval.

Possible disadvantages of Vespa.ai

  • Complexity
    The platform might have a steep learning curve for beginners due to its advanced features and wide range of capabilities, which can increase the onboarding time.
  • Resource Intensive
    Operating and maintaining the system can be resource-intensive, requiring significant computational resources, which might not be viable for small businesses.
  • Limited Community Support
    Although open-source, the community around Vespa.ai is not as large as some other platforms, potentially leading to slower times in community-driven support and updates.
  • Niche Use Cases
    It is specifically tailored for applications that need large-scale data processing and fast search capabilities, which might be more than necessary for simpler projects.
  • Complex Configuration
    Configuring Vespa.ai can be complex and time-consuming, requiring in-depth understanding and expertise, which can delay implementation.

Sphinx Search features and specs

  • High Performance
    Sphinx Search is optimized for high performance, allowing it to handle large datasets efficiently and perform searches quickly.
  • Full-Text Search
    It provides robust full-text search capabilities, including support for advanced search operators and ranking algorithms.
  • Scalability
    Designed to scale both vertically and horizontally, making it suitable for projects that need to accommodate growing data volumes.
  • Integration
    Sphinx can easily integrate with various programming languages and existing databases like MySQL, PostgreSQL, and more.
  • Open Source
    Being an open-source software, Sphinx provides flexibility in terms of customization and cost-effectiveness.

Possible disadvantages of Sphinx Search

  • Complex Configuration
    Configuring Sphinx Search can be complex and might require a steep learning curve for new users.
  • Limited Multi-Language Support
    While it offers some support for multiple languages, it may not have as comprehensive language handling capabilities as some other search engines.
  • Lack of Real-Time Indexing
    Sphinx is not inherently designed for real-time indexing, which can be a limitation for use cases requiring instant updates.
  • Community Support
    Although it has an active community, the support network is not as extensive as those for larger, more established platforms.
  • Feature Set
    The feature set might not be as extensive or modern compared to other search platforms that have more recent updates and enhancements.

Category Popularity

0-100% (relative to Vespa.ai and Sphinx Search)

Vespa.ai

Sphinx Search

Custom Search Engine
63 63%
Custom Search Engine
37% 37
Search Engine
63 63%
Search Engine
37% 37
Databases
100 100%
Databases
0% 0
Custom Search
0 0%
Custom Search
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Vespa.ai and Sphinx Search

Vespa.ai Reviews

We have no reviews of Vespa.ai yet.
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Sphinx Search Reviews

The most overlooked part in software development - writing project documentation
# Catch-all target: route all unknown targets to Sphinx using the new # "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS). %: Makefile @$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)import sys, os import sphinx_rtd_theme
Source: netgen.io
Elasticsearch vs. Solr vs. Sphinx: Best Open Source Search Platform Comparison
We will not make comparisons like Sphinx vs Solr, or Solr vs Sphinx, or Sphinx vs Elasticsearch as they all are decent competitors, with almost equal performance, scalability, and features. But each of them has specific peculiarities that can be influential for your project. Now, let’s take a look at which option can be better for your business.
Source: greenice.net

Social recommendations and mentions

Based on our record, Vespa.ai should be more popular than Sphinx Search. It has been mentiond 20 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.

Vespa.ai mentions (20)

  • Why You Shouldn’t Invest In Vector Databases?
    In cases where a company possesses a strong technological foundation and faces a substantial workload demanding advanced vector search capabilities, its ideal solution lies in adopting a specialized vector database. Prominent options in this domain include Chroma (having raised $20 million), Zilliz (having raised $113 million), Pinecone (having raised $138 million), Qdrant (having raised $9.8 million), Weaviate... - Source: dev.to / 11 days ago
  • Code Search Is Hard
    If you're serious about scaling up, definitely consider Vespa (https://vespa.ai). At serious scale, Vespa will likely knock all the other options out of the park. - Source: Hacker News / about 1 year ago
  • Simple Precision Time Protocol at Meta
    Yahoo released their geographic data catalogue under open license and it still lives on as https://whosonfirst.org/ Afaik https://en.wikipedia.org/wiki/Apache_ZooKeeper started at Yahoo https://vespa.ai/ was Yahoo's search engine for news and other content product, now spinned off (https://techcrunch.com/2023/10/04/yahoo-spins-out-vespa-its-search-tech-into-an-independent-company/). - Source: Hacker News / about 1 year ago
  • Are we at peak vector database?
    I think https://vespa.ai/ has the right approach in this space by focusing on being hybrid - vectors alone aren't great for production use cases, it's the combining of vectors+text that lets you use ranking to get meaningful result. (I'm an investor so I'm biased; but it's also the reason why I invested). - Source: Hacker News / over 1 year ago
  • Show HN: RAGatouille, a simple lib to use&train top retrieval models in RAG apps
    So what’s the catch? Why is this not everywhere? Because IR is not quite NLP — it hasn’t gone fully mainstream, and a lot of the IR frameworks are, quite frankly, a bit of a pain to work with in-production. Some solid efforts to bridge the gap like Vespa [1] are gathering steam, but it’s not quite there. [1] https://vespa.ai. - Source: Hacker News / over 1 year ago
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Sphinx Search mentions (10)

  • Best 5 Ecommerce Search Engines for Developers
    Sphinx is a search engine that can be integrated into a website to provide advanced search functionality such as full-text, Boolean, and faceted search. It is a powerful open-source search engine that can handle large amounts of data and quickly return results. - Source: dev.to / about 2 years ago
  • Question about embedding for search vs clustering applications
    Have been using Sphinx. It does some processing around suffixes, tenses, and so on, and looks at word proximity (BM25), but is definitely limited. Source: about 2 years ago
  • grep like search with preprocessing
    Lucene is the thing you think you need. Elastic Search is a nice wrapper for it. But these are Java, so maybe you want Sphinx Search (C++) or MeiliSearch (Rust). Source: over 2 years ago
  • Search MySQL table for multiple keywords and return number of occurrences for each keyword per row
    Using a natural language search will almost certainly be a better solution and PHP may not be the best tool for this task. Figure out how you are going to get the text out of the PDF and where you are going to put it. Look at things like sphinx and full text search in boolean mode for doing the keyword matching. Source: over 2 years ago
  • How to do a Scryfall-like search?
    In practice though you don't do any of this, you get a library to do it for you. I've used Sphinx Search in the past for some fairly hefty (In the order of terabytes), and there's a good book covering how to get it all set up and started. Source: almost 3 years ago
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What are some alternatives?

When comparing Vespa.ai and Sphinx Search, you can also consider the following products

Meilisearch - Ultra relevant, instant, and typo-tolerant full-text search API

ElasticSearch - Elasticsearch is an open source, distributed, RESTful search engine.

Typesense - Typo tolerant, delightfully simple, open source search 🔍

Apache Solr - Solr is an open source enterprise search server based on Lucene search library, with XML/HTTP and...

Milvus - Vector database built for scalable similarity search Open-source, highly scalable, and blazing fast.

Algolia - Algolia's Search API makes it easy to deliver a great search experience in your apps & websites. Algolia Search provides hosted full-text, numerical, faceted and geolocalized search.

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