Project Summary
Declarative large-scale machine learning (ML) that aims at flexible specification of ML algorithms and automatic generation of hybrid runtime plans ranging from single-node, in-memory computations, to distributed computations on Apache Hadoop and Apache Spark.
ML algorithms are expressed in an R-like or Python-like syntax that includes linear algebra primitives, statistical functions, and ML-specific constructs. This high-level language significantly increases the productivity of data scientists as it provides (1) full flexibility in expressing custom analytics, and (2) data independence from the underlying input formats and physical data representations. Automatic optimization according to data and cluster characteristics ensures both efficiency and scalability.
In a Nutshell, Apache SystemML...
- ...
- ...
-
...
has a well established, mature codebase
maintained by a very large development team
with decreasing Y-O-Y commits -
...
took an estimated 590 years of effort (COCOMO model)
starting with its first commit in January, 2012
ending with its most recent commit 8 days ago
Quick Reference
Apache License 2.0
Permitted
Commercial Use
Modify
Distribute
Place Warranty
Sub-License
Private Use
Use Patent Claims
Forbidden
Hold Liable
Use Trademarks
Required
Include Copyright
State Changes
Include License
Include Notice
These details are provided for information only. No information here is legal advice and should not be used as such.
This Project has No vulnerabilities Reported Against it
Did You Know...
-
...
in 2016, 47% of companies did not have formal process in place to track OS code
-
...
compare projects before you chose one to use
-
...
there are over 3,000 projects on the Open Hub with security vulnerabilities reported against them
-
...
you can subscribe to e-mail newsletters to receive update from the Open Hub blog
30 Day SummaryJan 11 2026 — Feb 10 2026
|
12 Month SummaryFeb 10 2025 — Feb 10 2026
|
