LynxKite is an open-source “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.
With LynxKite you can:
Import data (megabytes to terabytes) from a variety of sources. Work
directly with traditional data sources (CSV, JSON, ORC, Parquet files —
local or Hadoop, JDBC, Hive, etc.) or from a graph DB like Neo4j.
Turn data easily into graphs.
Use algorithms from a large library of graph operations, including
graph AI operations.
Put together complex data processing pipelines where you can
combine graph operations, classical data analysis operations and
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 "no code" GUI as well
as coding via powerful Python integration (code embedding, Python
API, code generation).
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.
LynxKite is to graph databases what RapidMiner and IBM SPSS Modeler
are 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.