CI/CD with Docker, and GitHub Actions for a TigerGraph-backed Gradle application.

Photo by Matt Dean via

Integration testing helps us verify that our applications work as expected when interacting with third-party software as they would in production. When integration testing involves the inclusion of a database, then this brings in its own array of configuration and set up.

How do the graph databases JanusGraph and TigerGraph compare to an industry-standard, PostgreSQL?

Photo by henry perks on Unsplash


The collection of spatio-temporal data is commonplace today — prime examples are user-generated data from mobile devices or social platforms, streams of sensor data from static or moving sensors, satellite or remote sensing data. To make sense of this vast volume of heterogeneous data, a variety of aggregation and fusion steps have to be applied to achieve semantic data enrichment for subsequent use in value-added services. However, enabling these enrichment steps generally relies on stable and highly scalable data handling and storage infrastructures. …

TigerGraph can be combined with Docker to run on nearly any OS. In this article, we tackle the issue of the large TigerGraph image and its unused potential.

Image by author. Logos are from TigerGraph and Docker’s websites respectively.

TigerGraph is my graph database and graph analytics platform of choice as it is fast, scalable, and has an active open-source community. I regularly make use of TigerGraph locally due to my location not having nearby TigerGraph Cloud servers.

  • Redhat and Centos versions 6.5–6.9, 7.0–7.4, and 8.0–8.2
  • Ubuntu 14.04, 16.04, and 18.04
  • Debian 8

For anyone using operating systems beyond this list, a logical solution would be to make use of containerization: Docker, in the case of this article.

David Baker Effendi

Computer science student at Stellenbosch University focusing on the application of graph-driven analytics

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