Graph Databases are NoSQL databases in which data is represented in the form of nodes and relationships between them. A wide variety of problems can be represented as graphs. Once the data is in a graph database, it can be queried for all sorts of insights, including properties of nodes, statistics, or paths between nodes. It is also possible to run algorithms from graph theory for more advanced analytics.
Below are some articles and other resources I have prepared about graph databases.
RedisGraph
Note: RedisGraph is being discontinued.
- First Steps with RedisGraph (9th November 2019)
- Family Tree with RedisGraph (17th November 2019)
- IOD Blog: RedisGraph: A Fresh Graph Database Based on Redis (Part 1) (22nd April 2020)
- IOD Blog: RedisGraph: A Fresh Graph Database Based on Redis (Part 2) (15th May 2020)
- Talk: A Practical Introduction to RedisGraph (2020) at RedisConf 2020
Memgraph
- Using the Neo4j Bolt Driver for Python with Memgraph (20th November 2022)
- Migrating Cartography to Memgraph (15th July 2023)
Neo4j
- Getting Started with Cartography for AWS (15th April 2022)
- Project Management is a Graph Problem (8th January 2023)
- Getting Started with Cartography for Okta (12th July 2023)