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Description

Apache Hive is a data warehouse solution that enables the efficient reading, writing, and management of substantial datasets stored across distributed systems using SQL. It allows users to apply structure to pre-existing data in storage. To facilitate user access, it comes equipped with a command line interface and a JDBC driver. As an open-source initiative, Apache Hive is maintained by dedicated volunteers at the Apache Software Foundation. Initially part of the Apache® Hadoop® ecosystem, it has since evolved into an independent top-level project. We invite you to explore the project further and share your knowledge to enhance its development. Users typically implement traditional SQL queries through the MapReduce Java API, which can complicate the execution of SQL applications on distributed data. However, Hive simplifies this process by offering a SQL abstraction that allows for the integration of SQL-like queries, known as HiveQL, into the underlying Java framework, eliminating the need to delve into the complexities of the low-level Java API. This makes working with large datasets more accessible and efficient for developers.

Description

Apache Mahout is an advanced and adaptable machine learning library that excels in processing distributed datasets efficiently. It encompasses a wide array of algorithms suitable for tasks such as classification, clustering, recommendation, and pattern mining. By integrating seamlessly with the Apache Hadoop ecosystem, Mahout utilizes MapReduce and Spark to facilitate the handling of extensive datasets. This library functions as a distributed linear algebra framework, along with a mathematically expressive Scala domain-specific language, which empowers mathematicians, statisticians, and data scientists to swiftly develop their own algorithms. While Apache Spark is the preferred built-in distributed backend, Mahout also allows for integration with other distributed systems. Matrix computations play a crucial role across numerous scientific and engineering disciplines, especially in machine learning, computer vision, and data analysis. Thus, Apache Mahout is specifically engineered to support large-scale data processing by harnessing the capabilities of both Hadoop and Spark, making it an essential tool for modern data-driven applications.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Apache Spark Yes 
Acceldata Yes 
Alteryx Yes 
Apache Ranger Yes 
Cloudera Data Platform Yes 
Dataiku Yes 
Datameer Yes 
Fosfor Decision Cloud Yes 
IBM watsonx.data Yes 
IRI CoSort Yes 
Mode Yes 
Precisely Connect Yes 
Qlik Staige Yes 
QueryPie Yes 
SAS Federation Server Yes 
SAS Studio Yes 
Stackable Yes 
Syntho Yes 
Varada Yes 
Yandex Data Proc Yes 

Integrations

Apache Spark Yes 
Acceldata No 
Alteryx No 
Apache Ranger No 
Cloudera Data Platform No 
Dataiku No 
Datameer No 
Fosfor Decision Cloud No 
IBM watsonx.data No 
IRI CoSort No 
Mode No 
Precisely Connect No 
Qlik Staige No 
QueryPie No 
SAS Federation Server No 
SAS Studio No 
Stackable No 
Syntho No 
Varada No 
Yandex Data Proc No 

Pricing Details

No price information available.
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 No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
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 Yes 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Apache Software Foundation

Founded

1999

Country

United States

Website

hive.apache.org

Vendor Details

Company Name

Apache Software Foundation

Country

United States

Website

mahout.apache.org

Product Features

ETL

Data Analysis No 
Data Filtering No 
Data Quality Control No 
Job Scheduling No 
Match & Merge No 
Metadata Management No 
Non-Relational Transformations No 
Version Control 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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