Memgraph 1.0

What it does

Memgraph is an in-memory graph database engineered to power real-time operational graph applications. Memgraph supports the Cypher and integrates deeply with the Python ecosystem to help you easily develop and deploy graph-based applications.

Experience high-performance graph computing with Memgraph — the scalable, in-memory graph database solution compatible with Neo4j.

Complement vector search with structured, connected context and traceable multi-hop reasoning across enterprise data in milliseconds. Standard RAG retrieves text chunks by similarity. GraphRAG traverses a knowledge graph to follow multi-hop relationships across entities, connecting information that similarity matching can't reach. LLMs are stateless. Vector-based memory retrieves what sounds similar, not what's structurally relevant. Memgraph stores and connects three types of long-term memory, semantic, episodic, and procedural, as a unified graph that any AI system can query in real time. The core question for any agent is: what should I do next? A reasoning graph makes the answer…from memgraph.com

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  Memgraph – Transactional, in-memory, cypher-compatible graph database2020 · memgraph.com · ▲89

  Memgraph 1.0 is now production-ready, offering high-performance, in-memory graph database with Cypher support.

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  Memgraph 2.2. is released – graph database that supports streaming2022 · memgraph.com · ▲14

  A few days ago we have released a new version of Memgraph. Memgraph is a streaming graph application platform that helps you wrangle your streaming data, build sophisticated models that you can query in real-time, and develop applications. It is powered by an in-memory graph database built to handle real-time use-cases at enterprise scale. Memgraph supports strongly-consistent ACID transactions and uses the standardized Cypher query language for structuring, manipulating, and exploring data. The main new things in Memgraph 2.2 are: - you can run Memgraph now on Apple M1 based computers - you…

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  We Built a Documentation Recommendation System Using Graph Database2022 · memgraph.com · ▲59

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  Muscle-Mem, a behavior cache for AI agents2025 · github.com · ▲226

  Hi HN! Erik here from Pig.dev, and today I'd like to share a new project we've just open sourced: Muscle Mem is an SDK that records your agent's tool-calling patterns as it solves tasks, and will deterministically replay those learned trajectories whenever the task is encountered again, falling back to agent mode if edge cases are detected. Like a JIT compiler, for behaviors. At Pig, we built computer-use agents for automating legacy Windows applications (healthcare, lending, manufacturing, etc). A recurring theme we ran into was that businesses already had RPA (pure-software scripts), and…

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  We have built a benchmark platform for graph databases2022 · memgraph.com · ▲83
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  Modeling Berlin subway lines in graph database2023 · memgraph.com · ▲29

  Explore the Berlin subway system using Memgraph Lab, mapping subway stops as nodes and connections as edges in a graph database.

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