StackShareStackShare
Follow on
StackShare

Discover and share technology stacks from companies around the world.

Follow on

© 2025 StackShare. All rights reserved.

Product

  • Stacks
  • Tools
  • Feed

Company

  • About
  • Contact

Legal

  • Privacy Policy
  • Terms of Service
  1. Stackups
  2. Utilities
  3. Task Scheduling
  4. Remote Server Task Execution
  5. Neptune vs StackStorm

Neptune vs StackStorm

OverviewComparisonAlternatives

Overview

StackStorm
StackStorm
Stacks80
Followers186
Votes31
GitHub Stars6.4K
Forks774
Neptune
Neptune
Stacks16
Followers38
Votes2

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs
CLI (Node.js)
or
Manual

Detailed Comparison

StackStorm
StackStorm
Neptune
Neptune

StackStorm is a platform for integration and automation across services and tools. It ties together your existing infrastructure and application environment so you can more easily automate that environment -- with a particular focus on taking actions in response to events.

It brings organization and collaboration to data science projects. All the experiement-related objects are backed-up and organized ready to be analyzed, reproduced and shared with others. Works with all common technologies and integrates with other tools.

Automations tie events to actions you’d like to take, using a rules engine and, if you want, comprehensive workflow. Automations are your operational patterns summarized as code.;StackStorm automations work either by starting with your existing scripts – just add simple meta data – or by authoring the automations within StackStorm.;Automations are the heart of StackStorm – they allow you to share operational patterns, boost productivity, and automate away the routine.;CLI, REST API + Python Bindings
Experiment tracking; Experiment versioning; Experiment comparison; Experiment monitoring; Experiment sharing; Notebook versioning
Statistics
GitHub Stars
6.4K
GitHub Stars
-
GitHub Forks
774
GitHub Forks
-
Stacks
80
Stacks
16
Followers
186
Followers
38
Votes
31
Votes
2
Pros & Cons
Pros
  • 7
    Auto-remediation
  • 5
    Integrations
  • 4
    Automation
  • 4
    Complex workflows
  • 3
    Open source
Cons
  • 3
    Complexity
  • 1
    There are not enough sources of information
Pros
  • 1
    Supports both gremlin and openCypher query languages
  • 1
    Aws managed services
Cons
  • 1
    Doesn't have proper clients for different lanuages
  • 1
    Doesn't have much support for openCypher clients
  • 1
    Doesn't have much community support
Integrations
Mailgun
Mailgun
VMware vSphere
VMware vSphere
Rackspace Cloud Servers
Rackspace Cloud Servers
Vault
Vault
Octopus Deploy
Octopus Deploy
Ansible
Ansible
Duo
Duo
PhantomJS
PhantomJS
Yammer
Yammer
Cassandra
Cassandra
PyTorch
PyTorch
Keras
Keras
R Language
R Language
MLflow
MLflow
Matplotlib
Matplotlib

What are some alternatives to StackStorm, Neptune?

TensorFlow

TensorFlow

TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.

scikit-learn

scikit-learn

scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.

PyTorch

PyTorch

PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.

Keras

Keras

Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/

Kubeflow

Kubeflow

The Kubeflow project is dedicated to making Machine Learning on Kubernetes easy, portable and scalable by providing a straightforward way for spinning up best of breed OSS solutions.

TensorFlow.js

TensorFlow.js

Use flexible and intuitive APIs to build and train models from scratch using the low-level JavaScript linear algebra library or the high-level layers API

Polyaxon

Polyaxon

An enterprise-grade open source platform for building, training, and monitoring large scale deep learning applications.

Streamlit

Streamlit

It is the app framework specifically for Machine Learning and Data Science teams. You can rapidly build the tools you need. Build apps in a dozen lines of Python with a simple API.

MLflow

MLflow

MLflow is an open source platform for managing the end-to-end machine learning lifecycle.

H2O

H2O

H2O.ai is the maker behind H2O, the leading open source machine learning platform for smarter applications and data products. H2O operationalizes data science by developing and deploying algorithms and models for R, Python and the Sparkling Water API for Spark.

Related Comparisons

GitHub
Bitbucket

Bitbucket vs GitHub vs GitLab

GitHub
Bitbucket

AWS CodeCommit vs Bitbucket vs GitHub

Kubernetes
Rancher

Docker Swarm vs Kubernetes vs Rancher

Postman
Swagger UI

Postman vs Swagger UI

gulp
Grunt

Grunt vs Webpack vs gulp