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RushDB Blog
Guides, fundamentals, engineering notes, product updates, and implementation blueprints for building AI memory and graph-backed applications with RushDB.
Latest Updates
Guides, fundamentals, engineering notes, product updates, and implementation blueprints for building AI memory and graph-backed applications with RushDB.
RushDB brings scoped, durable, lifecycle-aware memory to OpenClaw and Hermes Agent through native connectors and one shared event contract.
LLM applications naturally fragment into ETL, embedding, graph sync, search indexing, and metadata pipelines. Learn why this happens and how a single ingestion layer can replace.
Every new agent needs a prompt explaining your tables and fields. RushDB lets agents fetch a structured snapshot of the live graph at runtime.
RushDB 2.0 is a major release built for the agentic era: native semantic search, ontology-aware querying, MCP with OAuth, bring-your-own Neo4j, and prebuilt agent skills. It turns memory infrastructure into one unified layer, so developers can store structured context, traverse relationships, and search by meaning without stitching together multiple systems.
Discover how LMPG transforms graph databases by treating properties as first-class citizens rather than simple node attributes. This comprehensive technical guide explores RushDB's groundbreaking architecture that enables automatic schema evolution, property-first queries, and cross-domain analytics impossible in traditional property graphs or RDF systems.
Labeled Property Graphs (LPGs) represent an evolution of traditional property graphs, introducing explicit type labels for nodes and relationships. This enhancement not only improves schema clarity but also boosts query performance, making LPGs a preferred choice for complex data modeling scenarios. In this article, we explore the advantages, challenges, and practical applications of LPGs.
Resource Description Framework (RDF) represents a fundamental paradigm shift in how we model and represent knowledge on the web. As the cornerstone of the Semantic Web, RDF provides a standardized method for describing resources and their relationships in a way that is both machine-readable and semantically rich. Unlike traditional data models that focus on storage and retrieval efficiency, RDF prioritizes meaning, interoperability, and automated reasoning.
Complete guide to graph database models: property graphs, RDF, labeled graphs, and knowledge graphs. Learn which graph model fits your use case and how to choose the right technology.
See how a single line of code can replace an entire backend infrastructure while preserving your data's natural structure. Perfect for rapid prototyping, MVPs, and applications with evolving data models.
Learn how to run RushDB in self-hosted mode using Docker with either Neo4j Aura or a local container.
RushDB is a zero-config, graph-powered instant database with bulk semi-structured data ingestion, automatic normalization, and powerful querying