Memgraph
In-memory graph database used as the graph layer for GraphRAG pipelines and agent memory, with Cypher queries plus vector and text search.
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About Memgraph
Memgraph is listed in our memory & RAG category and is aimed at builders. In-memory graph database used as the graph layer for GraphRAG pipelines and agent memory, with Cypher queries plus vector and text search. Pricing, as the maker states it: Source-available + cloud. Maturity: Active. We last checked the official link on 2026-10-19.
Memgraph at a glance
- Category: Memory & RAG
- Built for: Developers and teams building with AI agents
- Pricing: Source-available + cloud (as the maker states it)
- GitHub: memgraph/memgraph · 4,625 stars (as of Oct 21, 2026)
- Latest release: v3.14.0, Oct 21, 2026
- Last commit: Oct 21, 2026
- Official site: memgraph.com
- Listed on AgentScout: Oct 19, 2026
Memgraph FAQ
What is Memgraph?
In-memory graph database used as the graph layer for GraphRAG pipelines and agent memory, with Cypher queries plus vector and text search.
How much does Memgraph cost?
Memgraph's pricing, as the maker states it: Source-available + cloud. Check the official site for current plans.
Where can I find Memgraph's source code?
On GitHub at memgraph/memgraph, which had 4,625 stars as of Oct 21, 2026. The latest release is v3.14.0 (Oct 21, 2026).
What are alternatives to Memgraph?
Similar tools include Chroma, seekdb, txtai, MemMachine, Acontext and UltraRAG.
Facts from our link-checked listing, the GitHub repository and the official site. See something wrong? Suggest an edit.
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Memgraph alternatives
Other memory & RAG tools in our directory. See all memory & RAG tools →
Chroma
Open-source search and vector database widely used for agent memory and RAG.
seekdb
AI-native search database for agent storage combining vector, text and structured data.
txtai
All-in-one Python framework for semantic search, LLM orchestration and agents built on an embeddings database of vector, graph and relational indexes.
MemMachine
Universal memory layer for AI agents.
Acontext
Memory layer that stores agent experience as reusable skills.
UltraRAG
Low-code MCP-based framework from OpenBMB for building and debugging complex RAG pipelines with visible reasoning logic.
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🧭 Task guides: SQL and database tools for research agents · RAG and document tools for research agents · RAG and document tools for agent memory
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