What is Memgraph?
Memgraph is a native fully distributed in-memory graph database built to handle real-time use-cases at enterprise scale. Memgraph supports strongly-consistent ACID transactions; and uses the standardized openCypher query language for structuring, manipulating, and exploring data.
Does being in-memory mean that Memgraph will lose all data upon system failure or restart?
No. Memgraph uses RAM as the primary storage for data. However, Memgraph continuously backs up data to disk with transaction logs and periodic snapshots. On restart, Memgraph uses the snapshot and log files to recover its state to what it was before shutting down.
How far have you scaled your system?
It depends on the dataset and the queries, in other words, the workload. On a single machine, Memgraph scales up to the size of the main memory. In a distributed system, the graph is automatically repartitioned in the background to improve query execution time and scalability.
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 the 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 firstname.lastname@example.org or get in touch with our team on our Forum.
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.
Does Memgraph offer a cloud graph database as a service?
Yes, we offer fully-managed Memgraph on our cloud infrastructure as a service. For more details please visit our cloud pages. In addition, Memgraph Playground is a testing environment where you can play with various graph datasets.
Do you support Tinkerpop API stacks?
Memgraph doesn’t support the Tinkerpop API stack because Tinkerpop is highly dependent on the Java stack. Memgraph is implemented in C/C++/Assembly with openCypher and the Bolt protocol as an interface. We have considered Tinkerpop integration, but at the moment it’s not one of our highest priorities.
How do you interface with the system?
Memgraph supports the openCypher query language to query the database instance. It’s a declarative query language designed to query graphs. Communication between clients and the database is done via the Bolt protocol. For the list of supported programming languages please take a look here.
How do you upgrade?
To do software upgrades the whole cluster has to go down. Before that data has to be migrated to a cluster with the newer version of Memgraph. At the moment, we offer no downtime upgrades, but that’s a feature which is high on our priority list. What we do offer is support when the upgrade is needed.
Can you implement custom Cypher procedures?
Memgraph supports extending the query language with user-written procedures. These procedures are grouped into modules, which can then be loaded on startup. Query modules can be implemented by using the Python API or C API. Take a look at our guide Implement custom query modules.
Why is my Memgraph instance relatively slow?
Label indexing is not enabled by default in Memgraph, i.e., Memgraph will not automatically index labeled data. Therefore, it is up to the user to perform the indexing explicitly. Visit the Reference guide to find out more about creating indexes.
What are the Cypher implementation differences compared to Neo4j?
Although we try to implement openCypher query language as closely to the language reference as possible, we had to make some changes to enhance the user experience. You can find the differences listed in the Cypher manual.