|Basic Database Features|
|Hybrid In‑Memory / On‑Disk Storage Engine||Core||Enterprise|
|Optimized for Low Latency and High‑Throughput||Core||Enterprise|
|Dynamic Graph Partitioning||Core||Enterprise|
|High Availability Replication Coming soon||Core||Enterprise|
|Cross Data Center Replication Coming soon||Core||Enterprise|
|Security and Compliance|
|Advanced Password Policies||Core||Enterprise|
|Fine‑Grained Access Control||Core||Enterprise|
|Data Encryption Coming soon||Core||Enterprise|
|Data Redaction Coming soon||Core||Enterprise|
|Full Activity Auditing||Core||Enterprise|
|Stack Overflow and Slack Community Support||Core||Enterprise|
|Business Hours Support||Core||9a.m. - 5p.m. GMT|
|Download Book a Demo|
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Frequently Asked Questions
Can Memgraph be deployed in the cloud?
Yes, Memgraph can be deployed in the cloud. Memgraph is designed to be portable, but currently available only on x86_64 architecture. All standard Linux distributions like CentOS, Debian, Ubuntu, RedHat are supported. Memgraph is also available on Docker. For any other platforms, please drop us an email at [email protected] or get in touch with our team on our Slack Channel.
What does the hardware footprint look like?
Memgraph uses ~50GB to store 100M nodes and 100M edges with one label and one property per each node and an edge type and one property per edge.
When is Memgraph a good choice?
Memgraph is well suited for applications that require real-time transactional capabilities on connected data. It is built from the ground up to deliver high-performance and concurrency on read and write queries at scale. Specific use-cases include:
- Distributed OLTP
- Heavy write operations
- Very low latency read and write workloads
- Large scale graphs with 100M+ entities and edges
When is Memgraph not a good choice?
Memgraph is not yet well suitable for heavy analytics / OLAP workloads.