History[01]

Memgraph is a graph database start-up that was founded in 2016 by Dominik Tomicevic and Marko Budiselic.

Checkpoints[04]

Snapshots are taken periodically during the entire runtime of Memgraph. When a snapshot is triggered, the whole data storage is written to disk. (Unsure about the kind of checkpoint for now.)

Concurrency Control[05]

Memgraph features full ACID-compliant transactions and strong consistency.

Data Model[01]

Memgraph's underlying data model is the property graph model. A property graph consists of nodes and relationships (or vertices and edges). Nodes can hold any number of properties (key-value pairs) and can be assigned labels that represent their roles within a particular domain. For example, a node with a label "person" could have properties such as "name" or "age." Relationships are directed connections between two nodes and contain properties (just like nodes) as well as a single edge type. For example, a relationship in a graph of people can have the edge type "friend of," and a property "since."

Foreign Keys[06]

Unlike in other DBMSs, relationships are of equal importance in the graph data model as the data itself. Thus foreign keys are not required to infer connections between entities.

Indexes[07]

The central part of Memgraph's index data structure is a highly-concurrent skip list.

Isolation Levels[01]

Memgraph’s implementation of MVCC provides snapshot isolation level.

Logging[04]

Memgraph uses write-ahead logging (WAL). (Unsure about logging scheme for now.)

Parallel Execution[01]

Memgraph features a distributed query planning and execution engine. Each plan is divided into two: a plan that will be executed on the machine where the query is received and a plan that will be executed on the other machines. Nodes are allowed to exchange data during the execution process.

Query Compilation

Query Execution[08]

The execution of the query proceeds iteratively (generating one entry of the result set at a time), with data flowing from the bottom-most logical operator(s) (the start of the pipeline) to the top-most logical operator(s) (the end of the pipeline).

Query Interface[09][10]

Memgraph supports the openCypher query language developed by Neo4j. It is a declarative language for querying graph databases. openCypher is an open-source project to standardize Cypher as the query language for graph processing.