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EVA DB VS Weaviate

Compare EVA DB VS Weaviate and see what are their differences

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EVA DB logo EVA DB

EVA AI-Relational Database System | SQL meets Deep Learning

Weaviate logo Weaviate

Welcome to Weaviate
  • EVA DB Landing page
    Landing page //
    2023-04-17

EVA is an open-source AI-relational database with first-class support for deep learning models. It aims to support AI-powered database applications that operate on both structured (tables) and unstructured data (videos, text, podcasts, PDFs, etc.) with deep learning models.

  • Weaviate Landing page
    Landing page //
    2023-05-10

EVA DB features and specs

No features have been listed yet.

Weaviate features and specs

  • Semantic Search
    Weaviate provides advanced semantic search capabilities, allowing users to perform searches based on meanings and concepts rather than just keyword matching, enhancing the accuracy and relevance of search results.
  • Scalability
    Weaviate is designed to handle large-scale data efficiently, making it suitable for enterprise-level applications that require processing big datasets.
  • Graph-Based
    It leverages a graph-based data model which is intuitive for representing complex relationships between entities, providing a more natural way to organize and query data.
  • Integration with AI/ML Models
    Weaviate can integrate with machine learning models to enrich data processing capabilities, such as text vectorization, which improves the precision of semantic search.
  • Open-Source Platform
    Being open-source, Weaviate encourages community-driven development and transparency, allowing users to contribute to and modify the software in accordance with their needs.

Possible disadvantages of Weaviate

  • Complexity
    The advanced features and configurations of Weaviate can introduce complexity which may require a steep learning curve for new users unfamiliar with graph databases or semantic search technologies.
  • Resource Intensive
    Running Weaviate at scale can require significant computational resources, which might be a consideration for organizations with limited infrastructure capabilities.
  • Maturity and Support
    As a relatively newer technology compared to other established database systems, Weaviate might have fewer community resources and third-party integrations available.
  • Use Case Specificity
    Weaviate's focus on semantic search might make it less suitable for applications that only require simple, traditional relational database features without the added complexity of semantic layer.

EVA DB videos

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Weaviate videos

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Introducing the Weaviate Vector Search Engine!

More videos:

  • Review - Weaviate + Haystack presented by Laura Ham (Harry Potter example!)

Category Popularity

0-100% (relative to EVA DB and Weaviate)

EVA DB

Weaviate

Databases
18 18%
Databases
82% 82
Search Engine
13 13%
Search Engine
87% 87
Utilities
0 0%
Utilities
100% 100
Custom Search Engine
19 19%
Custom Search Engine
81% 81

User comments

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Social recommendations and mentions

Based on our record, Weaviate seems to be a lot more popular than EVA DB. While we know about 37 links to Weaviate, we've tracked only 1 mention of EVA DB. 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.

EVA DB mentions (1)

  • Using EvaDB to build AI-enhanced apps
    EvaDB plugs AI into traditional SQL databases, so as a first step, we’ll need to install a database. For this article, we’ll use SQLite because it's fast enough for our tests and does not require a proper database server running somewhere. You may choose a different database, if you prefer. - Source: dev.to / over 1 year ago

Weaviate mentions (37)

  • Why gemini flash 2.0 might be the final boss for RAGs
    Explore open-source vector stores like Weaviate or Chroma if you’re still going the RAG route. - Source: dev.to / 7 days ago
  • 10 open-source MCPs that make your AI agents smarter than your team lead
    Weaviate — comes with built-in modules for semantic search. - Source: dev.to / 7 days ago
  • 6 retrieval augmented generation (RAG) techniques you should know
    The key difference lies in the retrieval mechanism. Vector databases focus on semantic similarity by comparing numerical embeddings, while graph databases emphasize relations between entities. Two solutions for graph databases are Neptune from Amazon and Neo4j. In a case where you need a solution that can accommodate both vector and graph, Weaviate fits the bill. - Source: dev.to / 21 days ago
  • 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 / 22 days ago
  • Retrieving Original Documents via Summaries with Weaviate and LangChain
    In this post, we'll explore how to achieve a similar result using Weaviate and its cross-references feature, integrated with LangChain. We'll leverage Weaviate's ability to create cross-references between data objects to efficiently retrieve original documents by querying their summaries. - Source: dev.to / 7 months ago
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What are some alternatives?

When comparing EVA DB and Weaviate, you can also consider the following products

txtai - AI-powered search engine

Qdrant - Qdrant is a high-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/

Zilliz - Data Infrastructure for AI Made Easy

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

pgvecto.rs - Scalable, Low-latency and Hybrid-enabled Vector Search in Postgres. Revolutionize Vector Search, not Database. - tensorchord/pgvecto.rs

Vespa.ai - Store, search, rank and organize big data

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