Azure Machine Learning vs Sumo Logic: What are the differences?
Azure Machine Learning: A fully-managed cloud service for predictive analytics. Azure Machine Learning is a fully-managed cloud service that enables data scientists and developers to efficiently embed predictive analytics into their applications, helping organizations use massive data sets and bring all the benefits of the cloud to machine learning; Sumo Logic: Cloud Log Management for Application Logs and IT Log Data. Cloud-based machine data analytics platform that enables companies to proactively identify availability and performance issues in their infrastructure, improve their security posture and enhance application rollouts. Companies using Sumo Logic reduce their mean-time-to-resolution by 50% and can save hundreds of thousands of dollars, annually. Customers include Netflix, Medallia, Orange, and GoGo Inflight.
Azure Machine Learning and Sumo Logic are primarily classified as "Machine Learning as a Service" and "Log Management" tools respectively.
Some of the features offered by Azure Machine Learning are:
- Designed for new and experienced users
- Proven algorithms from MS Research, Xbox and Bing
- First class support for the open source language R
On the other hand, Sumo Logic provides the following key features:
- Ability to collect data from on-premise sources, private/public/hybrid clouds, and SaaS/PaaS environments
- Real-time continuous query engine that constantly updates dashboards and reports for immediate visualization
- Anomaly detection engine that enables companies to proactively uncover events without writing rules
According to the StackShare community, Sumo Logic has a broader approval, being mentioned in 57 company stacks & 7 developers stacks; compared to Azure Machine Learning, which is listed in 12 company stacks and 8 developer stacks.