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features
design
support

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Description

Bigtop is a project under the Apache Foundation designed for Infrastructure Engineers and Data Scientists who need a thorough solution for packaging, testing, and configuring leading open source big data technologies. It encompasses a variety of components and projects, such as Hadoop, HBase, and Spark, among others. By packaging Hadoop RPMs and DEBs, Bigtop simplifies the management and maintenance of Hadoop clusters. Additionally, it offers an integrated smoke testing framework, complete with a collection of over 50 test files to ensure reliability. For those looking to deploy Hadoop from scratch, Bigtop provides vagrant recipes, raw images, and in-progress docker recipes. The framework is compatible with numerous Operating Systems, including Debian, Ubuntu, CentOS, Fedora, and openSUSE, among others. Moreover, Bigtop incorporates a comprehensive set of tools and a testing framework that evaluates various aspects, such as packaging, platform, and runtime, which are essential for both new deployments and upgrades of the entire data platform, rather than just isolated components. This makes Bigtop a vital resource for anyone aiming to streamline their big data infrastructure.

Description

IBM Analytics Engine offers a unique architecture for Hadoop clusters by separating the compute and storage components. Rather than relying on a fixed cluster with nodes that serve both purposes, this engine enables users to utilize an object storage layer, such as IBM Cloud Object Storage, and to dynamically create computing clusters as needed. This decoupling enhances the flexibility, scalability, and ease of maintenance of big data analytics platforms. Built on a stack that complies with ODPi and equipped with cutting-edge data science tools, it integrates seamlessly with the larger Apache Hadoop and Apache Spark ecosystems. Users can define clusters tailored to their specific application needs, selecting the suitable software package, version, and cluster size. They have the option to utilize the clusters for as long as necessary and terminate them immediately after job completion. Additionally, users can configure these clusters with third-party analytics libraries and packages, and leverage IBM Cloud services, including machine learning, to deploy their workloads effectively. This approach allows for a more responsive and efficient handling of data processing tasks.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Apache Spark Yes 
Hadoop Yes 
Acquia CDP No 
Apache HBase Yes 
Beats Yes 
Galileo No 
IBM Cloud Object Storage No 
Jenkins Yes 
Jira Yes 
MINT No 
RadiantOne No 
Switch Automation No 
ZARUS No 

Integrations

Apache Spark Yes 
Hadoop Yes 
Acquia CDP Yes 
Apache HBase No 
Beats No 
Galileo Yes 
IBM Cloud Object Storage Yes 
Jenkins No 
Jira No 
MINT Yes 
RadiantOne Yes 
Switch Automation Yes 
ZARUS Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

$0.014 per hour
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Apache Software Foundation

Founded

1999

Country

United States

Website

bigtop.apache.org

Vendor Details

Company Name

IBM

Founded

1911

Country

United States

Website

www.ibm.com/cloud/analytics-engine

Product Features

Software Testing

Automated Testing No 
Black-Box Testing No 
Dynamic Testing No 
Issue Tracking No 
Manual Testing No 
Quality Assurance Planning No 
Reporting / Analytics No 
Static Testing No 
Test Case Management No 
Variable Testing Methods No 
White-Box Testing No 

Product Features

Data Discovery

Contextual Search No 
Data Classification No 
Data Matching No 
False Positives Reduction No 
Self Service Data Preparation No 
Sensitive Data Identification No 
Visual Analytics No 

Data Visualization

Analytics No 
Content Management No 
Dashboard Creation No 
Filtered Views No 
OLAP No 
Relational Display No 
Simulation Models No 
Visual Discovery No 

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