Django MongoDB Backend Now Generally Available
We are pleased to announce that the Django MongoDB Backend is now generally available. Production-ready, tested, and performant for most common use cases, the package…
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This Week in Neo4j: Road to NODES, MCP, GraphRAG, BandtoBand and more
Welcome to This Week in Neo4j, your fix for news from the world of graph databases! This edition invites you to sharpen your graph skills…
Rewire Your Integration Strategy: A Graph-First Approach With Neo4j and AI
Integration has always been about more than just connecting systems; it’s about synchronizing people, processes, and data. Yet, the path is often riddled with complexity…
Online Recommendation Engines with CockroachDB
Recommendation engines have gained immense importance in today’s digital landscape. As global competition intensifies, businesses frequently leverage recommendation systems to enhance user experiences, drive engagement,…
GraphRAG in Action: A Simple Agent for Know-Your-Customer Investigations
Built with OpenAI’s Agents SDK, MCP, Ollama, and Neo4j In the world of financial services, Know-Your-Customer (KYC) and Anti-Money Laundering (AML) are critical defense lines against…
Streamlining Editorial Operations with Gen AI and MongoDB
Are you overwhelmed by the sheer volume of information and the constant pressure to produce content that truly resonates? Audiences constantly demand engaging and timely…
RoachFest 2025 Vegas: Build for Scale, Agility, and Performance
Across three continents, RoachFest 2025 keeps bringing us together. It’s where engineers, operators, data architects, and tech leaders get real about building for scale, agility,…
Driving Airport Efficiency with MongoDB and Dataworkz
In 2024, airports worldwide supported over 40 million flights.1 What these millions of flights translate to is intense activity on the ground, where in each…
From Legal Documents to Knowledge Graphs
This blog post was co-authored with Tuana Çelik Create a free graph database instance in Neo4j AuraDB Retrieval-augmented generation (RAG) has emerged as a powerful technique for…
RAG Tutorial: How to Build a RAG System on a Knowledge Graph
Building a retrieval-augmented generation (RAG application for your LLM doesn’t have to be hard, especially when you follow the right steps. Whether you’re a developer…
Converged Datastore for Agentic AI
As artificial intelligence evolves from simple query-response systems to sophisticated autonomous agents, a critical architectural challenge emerges: traditional data architectures weren’t designed for AI systems…
New Benchmark Tests Reveal Key Vector Search Performance Factors
Search at scale is challenging. As powerful as vector search is, it can be tough to know how to properly weigh key factors like accuracy,…
DPDP Act: India’s New Era in Data Protection and Privacy
India’s digital scene is evolving rapidly, with an increased focus on individual privacy and data protection, as evidenced by global standards like Europe’s GDPR. These…
Powering Long-Term Memory for Agents With LangGraph and MongoDB
We’re excited to introduce the MongoDB Store for LangGraph—a powerful integration that brings flexible and scalable long-term memory to AI agents. This new integration between…
Quickly Build a ReAct Agent With LangGraph and MCP
Learn how to incorporate local and MCP-hosted tools into your agents A common question I get working with clients is how to set up an agent…