The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning. Learn more →
Cugraph Alternatives
Similar projects and alternatives to cugraph
-
Memgraph
Open-source graph database, built for real-time streaming data, compatible with Neo4j.
-
-
WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
-
pygraphistry
PyGraphistry is a Python library to quickly load, shape, embed, and explore big graphs with the GPU-accelerated Graphistry visual graph analyzer
-
demo-news-recommendation
Discontinued Exploring News Recommendation With Neo4j GDS
-
-
graph-data-science
Source code for the Neo4j Graph Data Science library of graph algorithms.
-
gqlalchemy
GQLAlchemy is a library developed with the purpose of assisting in writing and running queries on Memgraph. GQLAlchemy supports high-level connection to Memgraph as well as modular query builder.
-
InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
-
-
-
python-graphblas
Python library for GraphBLAS: high-performance sparse linear algebra for scalable graph analytics
-
Scalix
Scalix is a data parallel compute library that automatically scales to the available compute resources.
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better cugraph alternative or higher similarity.
cugraph reviews and mentions
Posts with mentions or reviews of cugraph.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-09-14.
-
GraphBLAS
https://en.wikipedia.org/wiki/Sparse_matrix :
> The concept of sparsity is useful in combinatorics and application areas such as network theory and numerical analysis, which typically have a low density of significant data or connections. Large sparse matrices often appear in scientific or engineering applications when solving partial differential equations.
CuGraph has a NetworkX-like API, though only so many of the networkx algorithms are CUDA-optimized.
https://github.com/rapidsai/cugraph :
> cuGraph operates, at the Python layer, on GPU DataFrames, thereby allowing for seamless passing of data between ETL tasks in cuDF and machine learning tasks in cuML. Data scientists familiar with Python will quickly pick up how cuGraph integrates with the Pandas-like API of cuDF. Likewise, users familiar with NetworkX will quickly recognize the NetworkX-like API provided in cuGraph, with the goal to allow existing code to be ported with minimal effort into RAPIDS.
> While the high-level cugraph python API provides an easy-to-use and familiar interface for data scientists that's consistent with other RAPIDS libraries in their workflow, some use cases require access to lower-level graph theory concepts. For these users, we provide an additional Python API called pylibcugraph, intended for applications that require a tighter integration with cuGraph at the Python layer with fewer dependencies. Users familiar with C/C++/CUDA and graph structures can access libcugraph and libcugraph_c for low level integration outside of python.
/? sparse
-
[D] Seeking Advice - For graph ML, Neo4j or nah?
I feel like you would need to develop a custom solution which might in part store data in Neo4j but you will have to figure out how to efficiently pull the data you need to train your GNNs; and I think this tends to be the bottleneck since Graph DBs are not optimised for the kinds of queries you need for GNNs. For what it's worth, I wouldn't really bother with implementing a custom graph data structure (unless I was really keen) as there are some good implementations out there. Have you looked at cuGraph for example?
- WSL2 CUDA/CUDF issue : Unable to establish a shared memory space between system and Vram
-
A note from our sponsor - WorkOS
workos.com | 16 Apr 2024
Stats
Basic cugraph repo stats
6
1,566
9.6
4 days ago
rapidsai/cugraph is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of cugraph is Cuda.
SaaSHub - Software Alternatives and Reviews
SaaSHub helps you find the best software and product alternatives
www.saashub.com