ArangoDB Reviews

FalkorDB Reviews

ArangoDB mentions (6)

• MongoDB takes a swing at PostgreSQL after claiming wins against rival

  If you like the document db idea there are a lot of choices, especially https://arangodb.com/ which I think gets little attention because people who use it see it as a secret weapon. Too bad about the license though. Also https://couchdb.apache.org/ and https://developer.marklogic.com/. - Source: Hacker News / 9 months ago

• Which Database is Perfect for You? A Comprehensive Guide to MySQL, PostgreSQL, NoSQL, and More

  ArangoDB is a multi-model database that supports document, key-value, and graph data models with a unified query language. - Source: dev.to / 11 months ago

• Demonstrating ArangoDB VelocyPack: A High-Performance Binary Data Format

  In modern databases, efficient data serialization and deserialization are paramount to achieving high performance. ArangoDB, a multi-model database, addresses this need with its innovative binary data format, VelocyPack. This article delves into the intricacies of VelocyPack, demonstrating its advantages, usage, and how it enhances the performance of ArangoDB with code examples in Java and Rust. - Source: dev.to / 12 months ago

• How to choose the right type of database

  ArangoDB: A native multi-model database, it offers flexibility for documents, graphs, and key-values. This versatility makes it suitable for applications requiring a combination of these data models. - Source: dev.to / about 1 year ago

• Spidergram is a collection of tools my company Autogram has built or enabled over the past several years to support our work to automate content inventories for large websites: it's part web crawler, part domain model, and part mad science. We released the first public beta today.

  ArangoDB, a "multi-modal" database engine that stores arbitrary JSON documents like MongoDB, key/value data like Redis, and graph relationships like Neo4j — and lets you leverage all three kinds of data in a single query. Source: over 2 years ago

FalkorDB mentions (3)

• Semantic search alone won't solve relational queries in your LLM retrieval pipeline.

  Use a low-latency graph database: Integrate FalkorDB for its sparse matrix representation and optimized linear algebra-based traversals. Queries execute in milliseconds—critical for real-time AI interactions. - Source: dev.to / 2 months ago

• Graph database vs relational vs vector vs NoSQL

  In vector databases, data is stored as high-dimensional vector embeddings, which are numerical representations generated by machine learning models to capture the features of data. When querying, the input is converted into a vector embedding, and similarity searches are performed between the query vector and stored embeddings using distance metrics like cosine similarity or Euclidean distance to retrieve the most... - Source: dev.to / 2 months ago

• NoLiMA: GPT-4o achieve 99.3% accuracy in short contexts (<1K tokens), performance degrades to 69.7% at 32K tokens.

  For AI architects, integrating graph-native storage with LLMs isn’t optional—it’s imperative for building systems capable of robust, multi-hop reasoning at scale. - Source: dev.to / 3 months ago