Memgraph vs Amazon Neptune
A managed AWS graph service against a graph engine you control. The choice comes down to your operating model, and where the graph needs to run.
One engine. Or several managed services.
Go deeper on the comparison.
The one-pager for the summary. The whitepaper for write concurrency, streaming ingestion, query language depth, GraphRAG execution, multi-tenancy and deployment.
Memgraph vs Amazon Neptune
Headline advantages, a side-by-side comparison, and when to pick each database.
Read CheatsheetMemgraph vs Amazon Neptune: Key Advantages
Write concurrency, streaming ingestion, query language depth, GraphRAG execution, multi-tenancy and deployment, in full.
Download whitepaperWhere Memgraph is the better choice.
For AI workloads
Retrieval as versioned query code
Neptune offers managed GraphRAG through Bedrock Knowledge Bases. Memgraph expresses vector retrieval, traversal, filtering, ranking and context assembly as one Cypher query inside the database, customisable at every level, with an inspectable provenance trail for every answer.
Vector indexes without the ceiling
Neptune Analytics permits one vector index per graph, fixed dimension, set only at graph creation. Memgraph supports multiple indexes on nodes and relationships, with configurable dimensions, metrics, capacity and scalar formats, and 85% less memory for vector storage.
Text retrieval in the same query
Neptune Database adds full-text search by integrating Amazon OpenSearch Service, a separate service and a synchronization path. Memgraph's native text indexes participate directly in Cypher and Atomic GraphRAG pipelines.
For real-time workloads
One live graph, not a snapshot
Neptune Analytics runs algorithms on separate compute, loaded from a cluster, snapshot or S3. Memgraph switches between transactional and analytical storage modes inside the same engine, no second system to provision, pay for or keep in sync.
Write concurrency without range contention
AWS documents gap locks, false conflicts and required retry logic for concurrent Neptune writes. Memgraph's node- and relationship-level locking means unrelated updates don't contend over broader index ranges.
Streaming into the database itself
Memgraph consumes Kafka, Redpanda and Pulsar directly, with Python transformation modules converting messages into nodes and relationships before commit. No connector services or pipeline glue to operate.
For both
Tenant isolation and deployment freedom
Memgraph Enterprise runs isolated databases within one deployment, each with its own storage, permissions and memory limits. Neptune runs only on AWS, and AWS notes pooled tenant controls are not enforced at the database level.
Cypher, in full.
Neptune generally supports openCypher 9 but documents unsupported features and behavioural differences. Memgraph's Cypher is compatible with Neo4j's and extends it with BFS, DFS, weighted shortest path, all-shortest-path and K-shortest-path, with filtering, weighting and accumulators applied during traversal.
CypherBolt protocolLangChainLlamaindexMCPAWS MarketplaceHow to move data
Export and import
Export from Neptune to S3, import into Memgraph via LOAD CSV or the Memgraph Lab import wizard.
Migration guideQuery it where it lives
Memgraph Zero exposes relational, graph, document, warehouse and lakehouse systems through one federated GQL endpoint, without relocating the data.
Memgraph ZeroBuilt for real-time graph workloads.
“Memgraph gave us a more cost-effective way to build on the graph capabilities we already knew, with a minimal learning curve for our Python and R team.”
“Memgraph helped us capture the higher order relationships between genes, drugs, and clinical evidence to surface treatment possibilities like Temazepam and Ibuprofen.”
“Being in memory, Memgraph is fast and really performant. We score 3.5 million-plus clients daily, and the entire infrastructure runs start to end in two hours on average.”
Behind the Missions: How NASA Manages Talent with a People Knowledge Graph
Read case studyHEALTHCARE AIHow Cedars-Sinai Uses Memgraph for Knowledge-Driven Machine Learning in Alzheimer’s Research
Read case studyFRAUD DETECTIONHow Capitec Built a Graph-Powered Fraud Scoring Pipeline for 3.5M+ Daily Cases
Read case studySee how Memgraph compares for your workload.
Neptune fits organisations committed to AWS that want a fully managed service, RDF and SPARQL, or turnkey GraphRAG through Bedrock. Memgraph fits real-time, continuously changing graphs, and workloads that must run outside AWS.
