LynxKite

LynxKite is an open-sourced “one stop shop” graph data science platform. Graph Analytics and Graph AI are the next frontier of data science and will improve machine learning performance in various applications. LynxKite is to graph databases what e.g. RapidMiner or IBM SPSS Modeler is to SQL databases. But it is not necessary to have a graph database to use LynxKite as it manages its own internal graph data model. So LynxKite is not a Graph DB but it is a powerful complementary technology for Graph DBs if you have one already. With LynxKite you can: > Import data - small or terabytes of it - from a variety of sources working directly with your traditional data sources (relational databases, standard data files - local or Hadoop) or importing a graph directly from a Graph DB. > Construct, alter, tune and enrich your graph model interactively: > Easily turn imported data into graphs in a low-code/no-code environment. > Use algorithms from a large library of graph operations (100+), including Graph AI operations > Put together complex data processing pipelines where you can combine graph operations, "classical" data analysis operations and machine learning. > Discover graphs and interpret algorithm results interactively, at any stage or step of the calculations, easily experimenting with different approaches and tuning parameters > Seamlessly combine the benefits of a friendly graphical interface and coding via powerful Python integration (code embedding, Python API and code generation) > Define and ingest a graph into a graph database and then use LynxKite to interactively build and productize a complex, powerful graph analysis pipeline. This pipeline might push its result back to the graph DB for serving. > Accelerate adoption of Graph data modelling and analytics in your organization by creating your own tutorials or wizards that allows less experienced people to contribute and learn.