Software Alternatives, Accelerators & Startups

Salesforce IoT Cloud VS Open Data Hub

Compare Salesforce IoT Cloud VS Open Data Hub and see what are their differences

Salesforce IoT Cloud logo Salesforce IoT Cloud

Modernize your field service management software to deliver better onsite support and keep employees and customers informed every step of the way.

Open Data Hub logo Open Data Hub

OpenDataHub
  • Salesforce IoT Cloud Landing page
    Landing page //
    2023-06-26
  • Open Data Hub Landing page
    Landing page //
    2023-06-01

Salesforce IoT Cloud videos

Connected Products and Salesforce IoT Cloud - Transforming Customer Engagements

Open Data Hub videos

Open Data Hub Introduction

More videos:

  • Review - Fraud Detection Using Open Data Hub on Openshift
  • Review - Installing Open Data Hub on OpenShift 4.1

Category Popularity

0-100% (relative to Salesforce IoT Cloud and Open Data Hub)
Data Dashboard
82 82%
18% 18
Data Science And Machine Learning
IoT Platform
100 100%
0% 0
Data Science Tools
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Salesforce IoT Cloud and Open Data Hub

Salesforce IoT Cloud Reviews

Open Source Internet of Things (IoT) Platforms
Salesforce IoT cloud will help you to transform all data which is generated by the customers, partners, devices, and sensors into relevant actions. It has partner connectors like AWS, Cisco Systems, etc.

Open Data Hub Reviews

We have no reviews of Open Data Hub yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Open Data Hub seems to be more popular. It has been mentiond 3 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Salesforce IoT Cloud mentions (0)

We have not tracked any mentions of Salesforce IoT Cloud yet. Tracking of Salesforce IoT Cloud recommendations started around Mar 2021.

Open Data Hub mentions (3)

  • job scheduling for scientific computing on k8s?
    Perhaps have a look at OpenDataHub. While geared for Openshift, see if they solved some of your concerns. Source: about 1 year ago
  • Elyra 2.2: R support, updated CLI, and more
    A common approach is to deploy JupyterHub on Kubernetes and configure it for Elyra, like it is done in Open Data Hub on the Red Hat OpenShift Container platform. - Source: dev.to / over 3 years ago
  • Automate your machine learning workflow tasks using Elyra and Apache Airflow
    If you are interested in running pipelines on Apache Airflow on the Red Hat OpenShift Container Platform, take a look at Open Data Hub. Open Data Hub is an open source project (just like Elyra) that should include everything you need to start running machine learning workloads in a Kubernetes environment. - Source: dev.to / over 3 years ago

What are some alternatives?

When comparing Salesforce IoT Cloud and Open Data Hub, you can also consider the following products

AWS IoT - Easily and securely connect devices to the cloud.

IBM Watson Studio - Learn more about Watson Studio. Increase productivity by giving your team a single environment to work with the best of open source and IBM software, to build and deploy an AI solution.

Particle.io - Particle is an IoT platform enabling businesses to build, connect and manage their connected solutions.

TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

AWS IoT Core - Whether building a connected home application for home security or building an industrial application to proactively identify equipment breakdown, you can use AWS IoT Core to securely communicate with and gather data from your diverse fleet of IoT d…

C3 AI Suite - The C3 AI Suite uses a model-driven architecture to accelerate delivery and reduce the complexities of developing enterprise-scale AI applications.