Blazegraph vs. GraphDB vs. Graph Engine vs. Python Comparison Chart

Blazegraph™ DB is a ultra high-performance graph database supporting Blueprints and RDF/SPARQL APIs. It supports up to 50 Billion edges on a single machine. It is in production use for Fortune 500 customers such as EMC, Autodesk, and many others. It is supporting key Precision Medicine applications and has wide-spread usage for life science applications. It is used extensively to support Cyber analytics in commercial and government applications. It powers the Wikimedia Foundation's Wikidata Query Service. You can choose an executable jar, war file, or tar.gz distribution. Blazegraph is designed to be easy to use and get started. It ships without SSL or authentication by default for this reason. For production deployments, we strongly recommend you enable SSL, authentication, and appropriate network configurations. There are some helpful links below to enable you to do this.

Graph Engine (GE) is a distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine. The distributed RAM store provides a globally addressable high-performance key-value store over a cluster of machines. Through the RAM store, GE enables the fast random data access power over a large distributed data set. The capability of fast data exploration and distributed parallel computing makes GE a natural large graph processing platform. GE supports both low-latency online query processing and high-throughput offline analytics on billion-node large graphs. Schema does matter when we need to process data efficiently. Strongly-typed data modeling is crucial for compact data storage, fast data access, and clear data semantics. GE is good at managing billions of run-time objects of varied sizes. One byte counts as the number of objects goes large. GE provides fast memory allocation and reallocation with high memory ratios.