Software Alternatives, Accelerators & Startups

ArangoDB VS Weaviate

Compare ArangoDB VS Weaviate and see what are their differences

ArangoDB logo ArangoDB

A distributed open-source database with a flexible data model for documents, graphs, and key-values.

Weaviate logo Weaviate

Welcome to Weaviate
  • ArangoDB Landing page
    Landing page //
    2023-01-20
  • Weaviate Landing page
    Landing page //
    2023-05-10

ArangoDB features and specs

  • Graph DB: Yes

Weaviate features and specs

No features have been listed yet.

ArangoDB videos

ArangoDB and Foxx Framework, deeper dive. WHILT#17

Weaviate videos

Introducing the Weaviate Vector Search Engine!

More videos:

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

Category Popularity

0-100% (relative to ArangoDB and Weaviate)
Databases
89 89%
11% 11
Search Engine
0 0%
100% 100
NoSQL Databases
100 100%
0% 0
Utilities
0 0%
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 ArangoDB and Weaviate

ArangoDB Reviews

9 Best MongoDB alternatives in 2019
ArangoDB is a native multi-model DBMS system. It supports three data models with one database core and a unified query language AQL. Its query language is declarative which helps you to compare different data access patterns by using a single query.
Source: www.guru99.com
Top 15 Free Graph Databases
ArangoDB is a distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions. ArangoDB
ArangoDB vs Neo4j - What you can't do with Neo4j
Scalability needs and ArangoDB ArangoDB is cluster ready for graphs, documents and key/values. ArangoDB is suitable for e.g. recommendation engines, personalization, Knowledge Graphs or other graph-related use cases. ArangoDB provides special features for scale-up (Vertex-centric indices) and scale-out (SmartGraphs).

Weaviate Reviews

We have no reviews of Weaviate yet.
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Social recommendations and mentions

Based on our record, Weaviate should be more popular than ArangoDB. It has been mentiond 28 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.

ArangoDB mentions (4)

Weaviate mentions (28)

  • How to choose the right type of database
    Weaviate: An open-source, cloud-native vector database built for scalable and fast vector searches. It's particularly effective for semantic search applications, combining full-text search with vector search for AI-powered insights. - Source: dev.to / 4 months ago
  • 7 Vector Databases Every Developer Should Know!
    Weaviate is an open-source vector search engine with out-of-the-box support for vectorization, classification, and semantic search. It is designed to make vector search accessible and scalable, supporting use cases such as semantic text search, automatic classification, and more. - Source: dev.to / 4 months ago
  • Qdrant, the Vector Search Database, raised $28M in a Series A round
    Congrats to them! What have your experiences with vector databases been? I've been using https://weaviate.io/ which works great, but just for little tech demos, so I'm not really sure how to compare one versus another or even what to look for really. - Source: Hacker News / 5 months ago
  • How Modern SQL Databases Are Changing Web Development - #4 Into the AI Era
    A RAG implementation's quality and performance highly depend on the similarity-based search of embeddings. The challenge arises from the fact that embeddings are usually high-dimensional vectors, and the knowledge base may have many documents. It's not surprising that the popularity of LLM catalyzed the development of specialized vector databases like Pinecone and Weaviate. However, SQL databases are also evolving... - Source: dev.to / 6 months ago
  • Make Notion search great again: Vector Database
    To find semantically similar texts we need to calculate the distance between vectors. While we have just a few short texts we can brute-force it: calculate the distance between our query and each text embedding one by one and see which one is the closest. When we deal with thousands or even millions of entries in our database, however, we need a more efficient way of comparing vectors. Just like for any other way... - Source: dev.to / 7 months ago
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What are some alternatives?

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

Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.

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/

MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.

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

neo4j - Meet Neo4j: The graph database platform powering today's mission-critical enterprise applications, including artificial intelligence, fraud detection and recommendations.

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