Memgraph
In-memory graph database for real-time AI systems and analytics
- Also known as
- memgraph
Available worldwide
What is Memgraph?
A high-performance, in-memory database designed for real-time graph queries and reasoning in AI applications. It combines sub-millisecond traversals with native vector search, ACID transactions, and streaming data connectors for fraud detection, network analysis, and AI augmentation.
Memgraph pricing
Plans, per-tier features and add-ons, dated and linked to live pricing. Pricing changes often; always verify at source before you rely on it.
Community Edition is free. Enterprise and managed cloud pricing available upon request.
Community Edition
FreeFully functional community edition, free forever
- Cypher query language
- Python client libraries
- LangChain and LlamaIndex integrations
- 40+ graph algorithms
What Memgraph does
The capabilities that matter for graph databases, normalised so it lines up with every alternative. “-” means we haven't confirmed it, not that it's missing.
- Graph model
- Property graph
- Query language(s)
- Cypher
- ACID transactions
- Full
- Consistency model
- Strong
- Storage
- Native graph
- Distributed / scale
- Clustered
- Replication / HA
- ✓
- OLTP vs OLAP
- Both
- Deployment
- Self-hosted
- Full-text search
- Built-in
- Built-in vector search
- ✓
- Licence class
- Permissive OSS
- openCypher / TinkerPop standard
- ✓
Platform & deployment
Independently observed- CLI
- macOS
- Web
- Linux
- Windows
- Cloud / SaaS
- Self-hosted
Integrations (15)
Independently observed- LangChain←•
- LlamaIndex←•
- OpenAI→•
- Cohere→•
- Apache Spark⇄
- Kerberos←•
- LDAP←•
- MCP⇄•
- LiteLLM→
- Kafka
- Pulsar
- Redpanda
- Cognee
- AWS (via Marketplace)
- Neo4j⇄
Security & compliance
Known vulnerabilities: 0 (0 in the last 12 months) sourcea count reflects scale & disclosure, not quality
Memgraph FAQ
Common questions about Memgraph, answered from independent, dated evidence.
What is Memgraph?
A high-performance, in-memory database designed for real-time graph queries and reasoning in AI applications. It combines sub-millisecond traversals with native vector search, ACID transactions, and streaming data connectors for fraud detection, network analysis, and AI augmentation. It is indexed under Graph Databases.
Source: https://memgraph.com/pricing
Is Memgraph free?
Memgraph offers a free tier, so you can start without paying. Paid plans are also available: Community Edition, Enterprise Edition – AI Platform, Enterprise Edition – Graph Analytics and Memgraph Cloud. Pricing changes often, so verify at source before relying on it.
Source: https://memgraph.com/pricing
What platforms does Memgraph support?
Memgraph supports the web and a command-line interface. Platforms we have not confirmed are simply not listed here rather than ruled out.
Source: https://memgraph.com/pricing
Can Memgraph be self-hosted?
Yes. Memgraph can be deployed cloud / SaaS, on-premise and self-hosted, so it does not have to run on the vendor's infrastructure.
Source: https://memgraph.com/pricing
What does Memgraph integrate with?
We have confirmed 5 integrations for Memgraph, including Kafka, Pulsar, Redpanda, Cognee and AWS (via Marketplace). This is what we could verify from public sources, so the vendor may support others we have not indexed.
Source: https://memgraph.com/pricing
What security certifications does Memgraph have?
We have independently confirmed GDPR for Memgraph. Certifications we do not list are ones we have not been able to verify from public sources, which is not the same as Memgraph not holding them. Always confirm compliance directly before you rely on it.
Where is Memgraph available?
Memgraph is available worldwide. Its primary markets are the United States and the EU. The vendor is headquartered in Croatia.
Source: https://memgraph.com/pricing
Memgraph alternatives
Other graph databases we track, ranked by the same independent score.
- Amazon NeptuneAuto-scaling graph database that improves generative AI accuracy through relationship datamedium · 73%
- FalkorDBA graph database for building AI applications with vector search and multi-tenant supportmedium · 64%
- Neo4jA graph database platform for modeling data relationships and powering AI applicationsmedium · 69%
- JanusGraphA distributed, open-source graph database built for massive scalemedium · 67%
- OrientDBAn integrated data platform supporting graphs, documents, and searchhigh · 77%
- DgraphAn open-source, distributed database for managing large-scale graph data with real-time query performancemedium · 60%
Compare Memgraph
Side by side against other graph databases, attribute by attribute, with a source on every value.
The vioscaleAI score: one lens on the evidence
Not user reviews and not a paid placement: a confidence-weighted blend of the independent signals below (adoption, activity, security posture, and more), which you can sort and re-weight yourself. Vendors can correct their listing but can never move their rank, and stars are weighted low as a vanity metric. It is one way to read the evidence for Memgraph, not the verdict.
| Signal | Score | Weight | Contribution | Evidence |
|---|---|---|---|---|
| Development activity | 63 | 0.14 | 8.5 | ✓ |
| Release cadence | 90 | 0.08 | 7.3 | ✓ |
| Capabilities | 58 | 0.08 | 4.6 | ✓ |
| Stars | 69 | 0.05 | 3.2 | ✓ |
| Integrations | 29 | 0.05 | 1.6 | ✓ |
| Dependent projects | 0 | 0.05 | 0.0 | ✓ |
| Security posture | 5 | 0.12 | 0.0 | - |
| Package downloads | 0 | 0.04 | 0.0 | - |
| Security score | 0 | 0.05 | 0.0 | - |
| Developer Q&A activity | 0 | 0.14 | 0.0 | - |
Computed . Re-weight it by intent, or see the full method.
All data & sourcesshow ↓
Every value we hold, with its source, retrieval date, and confidence. This is the evidence behind the score: don't trust it, verify it.
Activity
| Attribute | Value | Evidence |
|---|---|---|
| Commits last 30d | 100 | mediumsource · 2026-10-15 · 65% |
Adoption
Content
| Attribute | Value | Evidence |
|---|---|---|
| Faq | 7 items | mediumsource · 2026-09-10 · 64% |
Features
| Attribute | Value | Evidence |
|---|---|---|
| Capabilities | Storage: native · Workload: both · Deployment: self_hosted · Consistency: strong · Distributed: clustered · Graph model: property_graph | mediumsource · 2026-10-15 · 60% |
Integrations
| Attribute | Value | Evidence |
|---|---|---|
| Count | 9 | mediumsource · 2026-10-15 · 60% |
Language
| Attribute | Value | Evidence |
|---|---|---|
| Primary | C++ | highsource · 2026-10-15 · 90% |
Market
| Attribute | Value | Evidence |
|---|---|---|
| Availability | PrimaryMarkets: … · AvailabilityScope: global · AvailableCountries: … · NotAvailableCountries: … | highsource · 2026-10-15 · 75% |
Pricing
Release
Security
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