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features
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support

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Write a Review

Description

Apache Giraph is a scalable iterative graph processing framework designed to handle large datasets efficiently. It has gained prominence at Facebook, where it is employed to analyze the intricate social graph created by user interactions and relationships. Developed as an open-source alternative to Google's Pregel, which was introduced in a seminal 2010 paper, Giraph draws inspiration from the Bulk Synchronous Parallel model of distributed computing proposed by Leslie Valiant. Beyond the foundational Pregel model, Giraph incorporates numerous enhancements such as master computation, sharded aggregators, edge-focused input methods, and capabilities for out-of-core processing. The ongoing enhancements and active support from a growing global community make Giraph an ideal solution for maximizing the analytical potential of structured datasets on a grand scale. Additionally, built upon the robust infrastructure of Apache Hadoop, Giraph is well-equipped to tackle complex graph processing challenges efficiently.

Description

The Apache Hadoop software library serves as a framework for the distributed processing of extensive data sets across computer clusters, utilizing straightforward programming models. It is built to scale from individual servers to thousands of machines, each providing local computation and storage capabilities. Instead of depending on hardware for high availability, the library is engineered to identify and manage failures within the application layer, ensuring that a highly available service can run on a cluster of machines that may be susceptible to disruptions. Numerous companies and organizations leverage Hadoop for both research initiatives and production environments. Users are invited to join the Hadoop PoweredBy wiki page to showcase their usage. The latest version, Apache Hadoop 3.3.4, introduces several notable improvements compared to the earlier major release, hadoop-3.2, enhancing its overall performance and functionality. This continuous evolution of Hadoop reflects the growing need for efficient data processing solutions in today's data-driven landscape.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

AnalyticsCreator No 
Apache Sentry No 
BicDroid No 
Cloudera Data Platform No 
Determined AI No 
HyperCube No 
IBM watsonx.data No 
Informatica Dynamic Data Masking No 
LightBeam.ai No 
Mage Static Data Masking No 
MongoDB No 
NVMesh No 
NXLog No 
Normalyze No 
SnapLogic No 
Trino No 
Zuar Runner No 
iFinder No 

Integrations

AnalyticsCreator Yes 
Apache Sentry Yes 
BicDroid Yes 
Cloudera Data Platform Yes 
Determined AI Yes 
HyperCube Yes 
IBM watsonx.data Yes 
Informatica Dynamic Data Masking Yes 
LightBeam.ai Yes 
Mage Static Data Masking Yes 
MongoDB Yes 
NVMesh Yes 
NXLog Yes 
Normalyze Yes 
SnapLogic Yes 
Trino Yes 
Zuar Runner Yes 
iFinder Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
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 No 

Types of Training

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

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

giraph.apache.org

Vendor Details

Company Name

Apache Software Foundation

Founded

1999

Country

United States

Website

hadoop.apache.org

Product Features

Product Features

Big Data

Collaboration No 
Data Blends No 
Data Cleansing No 
Data Mining No 
Data Visualization No 
Data Warehousing No 
High Volume Processing No 
No-Code Sandbox No 
Predictive Analytics No 
Templates No 

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