I am looking for a sparse matrix library in Java that can do multiplications on sparse integer matrices, where the matrices represent the adjacency relations of a graph. The requirement is roughly the following: the library should be able to load and multiply a few matrices of 10M×10M elements, containing approx. 5M non-zero elements each, when running on a commodity machine (~16 GBs of RAM). The Eigen library for C++ satisfies this requirement. However, I couldn't find a good alternative for Java.

I looked at the following libraries:

I have also found a comprehensive survey at https://java-matrix.org/, created by the author of UJMP, which shows the state of the art in ~2015 and highlights that very few libraries support sparse matrices.

See also the GitHub issue on the performance of sparse matrix multiplication in MTJ.

A related question for a C/C++ library from 2010: Looking for a C/C++ interface for efficient computation of huge sparse matrix in Linux


There are two libraries I can recommend. Both support sparse matrices, including matrix-matrix multiplication, matrix-matrix element-wise multiplication and matrix-vector multiplication. Both are open-source, actively maintained, and available from the Maven Central.

  1. EJML (Efficient Java Matrix Library) is Apache-licensed (ASLv2) - [source code], [Maven]

  2. ojAlgo ("oj! Algorithms") is MIT-licensed - [source code], [Maven].

For the sparse workloads I tested, EJML had far superior performance, so it's worth trying that one first.

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