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  1. Stackups
  2. DevOps
  3. Log Management
  4. Log Management
  5. Azure Machine Learning vs Sumo Logic

Azure Machine Learning vs Sumo Logic

OverviewComparisonAlternatives

Overview

Sumo Logic
Sumo Logic
Stacks192
Followers282
Votes21
Azure Machine Learning
Azure Machine Learning
Stacks241
Followers373
Votes0

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.

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Detailed Comparison

Sumo Logic
Sumo Logic
Azure Machine Learning
Azure Machine Learning

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 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.

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;LogReduce, our pattern-recognition engine, that distills tens/hundreds of thousands of log messages into a set of patterns for easier issue identification and resolution;The ability to support data bursts on-demand with our elastic log processing architecture;Real-time alerts and notifications
Designed for new and experienced users;Proven algorithms from MS Research, Xbox and Bing;First class support for the open source language R;Seamless connection to HDInsight for big data solutions;Deploy models to production in minutes;Pay only for what you use. No hardware or software to buy
Statistics
Stacks
192
Stacks
241
Followers
282
Followers
373
Votes
21
Votes
0
Pros & Cons
Pros
  • 11
    Search capabilities
  • 5
    Live event streaming
  • 3
    Pci 3.0 compliant
  • 2
    Easy to setup
Cons
  • 2
    Expensive
  • 1
    Occasionally unreliable log ingestion
  • 1
    Missing Monitoring
No community feedback yet
Integrations
Amazon CloudFront
Amazon CloudFront
Amazon S3
Amazon S3
Akamai
Akamai
AWS CloudTrail
AWS CloudTrail
Microsoft Azure
Microsoft Azure

What are some alternatives to Sumo Logic, Azure Machine Learning?

Papertrail

Papertrail

Papertrail helps detect, resolve, and avoid infrastructure problems using log messages. Papertrail's practicality comes from our own experience as sysadmins, developers, and entrepreneurs.

Logmatic

Logmatic

Get a clear overview of what is happening across your distributed environments, and spot the needle in the haystack in no time. Build dynamic analyses and identify improvements for your software, your user experience and your business.

Loggly

Loggly

It is a SaaS solution to manage your log data. There is nothing to install and updates are automatically applied to your Loggly subdomain.

Logentries

Logentries

Logentries makes machine-generated log data easily accessible to IT operations, development, and business analysis teams of all sizes. With the broadest platform support and an open API, Logentries brings the value of log-level data to any system, to any team member, and to a community of more than 25,000 worldwide users.

Logstash

Logstash

Logstash is a tool for managing events and logs. You can use it to collect logs, parse them, and store them for later use (like, for searching). If you store them in Elasticsearch, you can view and analyze them with Kibana.

Graylog

Graylog

Centralize and aggregate all your log files for 100% visibility. Use our powerful query language to search through terabytes of log data to discover and analyze important information.

Sematext

Sematext

Sematext pulls together performance monitoring, logs, user experience and synthetic monitoring that tools organizations need to troubleshoot performance issues faster.

Fluentd

Fluentd

Fluentd collects events from various data sources and writes them to files, RDBMS, NoSQL, IaaS, SaaS, Hadoop and so on. Fluentd helps you unify your logging infrastructure.

ELK

ELK

It is the acronym for three open source projects: Elasticsearch, Logstash, and Kibana. Elasticsearch is a search and analytics engine. Logstash is a server‑side data processing pipeline that ingests data from multiple sources simultaneously, transforms it, and then sends it to a "stash" like Elasticsearch. Kibana lets users visualize data with charts and graphs in Elasticsearch.

Splunk

Splunk

It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.

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