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features
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support

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Description

Utilize Apache HBase™ when you require immediate and random read/write capabilities for your extensive data sets. This initiative aims to manage exceptionally large tables that can contain billions of rows across millions of columns on clusters built from standard hardware. It features automatic failover capabilities between RegionServers to ensure reliability. Additionally, it provides an intuitive Java API for client interaction, along with a Thrift gateway and a RESTful Web service that accommodates various data encoding formats, including XML, Protobuf, and binary. Furthermore, it supports the export of metrics through the Hadoop metrics system, enabling data to be sent to files or Ganglia, as well as via JMX for enhanced monitoring and management. With these features, HBase stands out as a robust solution for handling big data challenges effectively.

Description

MLlib, the machine learning library of Apache Spark, is designed to be highly scalable and integrates effortlessly with Spark's various APIs, accommodating programming languages such as Java, Scala, Python, and R. It provides an extensive range of algorithms and utilities, which encompass classification, regression, clustering, collaborative filtering, and the capabilities to build machine learning pipelines. By harnessing Spark's iterative computation features, MLlib achieves performance improvements that can be as much as 100 times faster than conventional MapReduce methods. Furthermore, it is built to function in a variety of environments, whether on Hadoop, Apache Mesos, Kubernetes, standalone clusters, or within cloud infrastructures, while also being able to access multiple data sources, including HDFS, HBase, and local files. This versatility not only enhances its usability but also establishes MLlib as a powerful tool for executing scalable and efficient machine learning operations in the Apache Spark framework. The combination of speed, flexibility, and a rich set of features renders MLlib an essential resource for data scientists and engineers alike.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Apache Spark Yes 
Amazon EMR Yes 
Apache Cassandra No 
Apache HBase No 
Apache Hive No 
Apache Knox Yes 
Apache Mesos No 
Apache PredictionIO Yes 
Apache Zeppelin Yes 
Azure HDInsight Yes 
Hackolade Yes 
IBM InfoSphere Information Server Yes 
IRI DarkShield Yes 
Java No 
Kubernetes No 
MLlib Yes 
Mage Sensitive Data Discovery Yes 
RazorSQL Yes 
Salesforce Data 360 Yes 

Integrations

Apache Spark Yes 
Amazon EMR No 
Apache Cassandra Yes 
Apache HBase Yes 
Apache Hive Yes 
Apache Knox No 
Apache Mesos Yes 
Apache PredictionIO No 
Apache Zeppelin No 
Azure HDInsight No 
Hackolade No 
IBM InfoSphere Information Server No 
IRI DarkShield No 
Java Yes 
Kubernetes Yes 
MLlib No 
Mage Sensitive Data Discovery No 
RazorSQL No 
Salesforce Data 360 No 

Pricing Details

Free, Open Source Software
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version 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 

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 No 

Customer Support

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

Types of Training

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

Types of Training

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

Vendor Details

Company Name

The Apache Software Foundation

Founded

1999

Country

United States

Website

hbase.apache.org

Vendor Details

Company Name

Apache Software Foundation

Founded

1995

Country

United States

Website

spark.apache.org/mllib/

Product Features

NoSQL Database

Auto-sharding Yes 
Automatic Database Replication No 
Data Model Flexibility Yes 
Deployment Flexibility Yes 
Dynamic Schemas Yes 
Integrated Caching Yes 
Multi-Model No 
Performance Management No 
Security Management No 

Product Features

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

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