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What is IBM Analytics Engine?

IBM Analytics Engine presents an innovative structure for Hadoop clusters by distinctively separating the compute and storage functionalities. Instead of depending on a static cluster where nodes perform both roles, this engine allows users to tap into an object storage layer, like IBM Cloud Object Storage, while also enabling the on-demand creation of computing clusters. This separation significantly improves the flexibility, scalability, and maintenance of platforms designed for big data analytics. Built upon a framework that adheres to ODPi standards and featuring advanced data science tools, it effortlessly integrates with the broader Apache Hadoop and Apache Spark ecosystems. Users can customize clusters to meet their specific application requirements, choosing the appropriate software package, its version, and the size of the cluster. They also have the flexibility to use the clusters for the duration necessary and can shut them down right after completing their tasks. Furthermore, users can enhance these clusters with third-party analytics libraries and packages, and utilize IBM Cloud services, including machine learning capabilities, to optimize their workload deployment. This method not only fosters a more agile approach to data processing but also ensures that resources are allocated efficiently, allowing for rapid adjustments in response to changing analytical needs.

What is Apache Mesos?

Mesos operates on principles akin to those of the Linux kernel; however, it does so at a higher abstraction level. Its kernel spans across all machines, enabling applications like Hadoop, Spark, Kafka, and Elasticsearch by providing APIs that oversee resource management and scheduling for entire data centers and cloud systems. Moreover, Mesos possesses native functionalities for launching containers with Docker and AppC images. This capability allows both cloud-native and legacy applications to coexist within a single cluster, while also supporting customizable scheduling policies tailored to specific needs. Users gain access to HTTP APIs that facilitate the development of new distributed applications, alongside tools dedicated to cluster management and monitoring. Additionally, the platform features a built-in Web UI, which empowers users to monitor the status of the cluster and browse through container sandboxes, improving overall operability and visibility. This comprehensive framework not only enhances user experience but also positions Mesos as a highly adaptable choice for efficiently managing intricate application deployments in diverse environments. Its design fosters scalability and flexibility, making it suitable for organizations of varying sizes and requirements.

Media

Media

Integrations Supported

Apache Spark
Galileo
Hadoop
IBM Cloud Object Storage
MINT
RadiantOne
Switch Automation

Integrations Supported

Apache Spark
Apache Aurora
Apache Flink
Fidelis Halo
Kapacitor
MLlib
Marathon
Netdata
OpsMx Enterprise for Spinnaker
Pliant
Riak TS
SolarWinds AppOptics
Tungsten Fabric
witboost

API Availability

API Availability

Pricing Information

$0.014 per hour
Free Version

Pricing Information

Pricing not provided
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS
Windows
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

IBM

Date Founded

1911

Company Location

United States

Company Website

www.ibm.com/cloud/analytics-engine

Company Facts

Organization Name

Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

mesos.apache.org

Categories and Features

Data Discovery

Not specified

Data Visualization

Not specified

Categories and Features

Cloud Management

Not specified

Cluster Management

Not specified

Container Engines

Not specified

Container Management

Not specified

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