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Version: Unreleased 🚧

Database functionalities overview

Articles within this section serve as a cookbook for getting things done as fast as possible. These articles tend to provide a step-by-step guide on using certain Memgraph features or solving a particular problem.

Streams

Memgraph can connect to existing Kafka, Pulsar and Redpanda streams. The streams use user-defined transformations to produce Cypher queries based on the received messages. To learn more about streams and transformations take a look at the following pages:

Inspect and profile Cypher queries

Memgraph also enables you to inspect and profile the execution of a query and get a detailed report on how the query's plan behaved. Take a look at the guides:

Machine learning

Memgraph TensorFlow op wraps the high-performance Memgraph client for use with TensorFlow, allowing natural data transfer between Memgraph and TensorFlow at any point of the model. If you are interested in using Memgraph for machine learning purposes take a look at:

Query modules

Memgraph supports extending the query language with user-written procedures. These procedures are grouped into modules, which can then be loaded either on startup or later on. To learn more about query modules take a look at the following guides:

Replication

Memgraph supports replication and the following guide demonstrates how to create a simple cluster of nodes running Memgraph instances:

Backup

Memgraph comes with a couple of queries that allow you to safely make a backup of the files containing its data:

User privileges

Memgraph comes with the option of granting, denying, or revoking a certain set of privileges to users or groups of users. To learn more visit:

Authentication and authorization

Memgraph supports authentication and (optional) authorization using a custom-built external auth module. To learn more visit:

Triggers

Memgraph supports running openCypher statements after a certain event happens during transaction execution, i.e. triggers: