Apache Accumulo

Apache Accumulo

Apache Corporation
MLlib

MLlib

Apache Software Foundation
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About

With Apache Accumulo, users can store and manage large data sets across a cluster. Accumulo uses Apache Hadoop's HDFS to store its data and Apache ZooKeeper for consensus. While many users interact directly with Accumulo, several open source projects use Accumulo as their underlying store. To learn more about Accumulo, take the Accumulo tour, read the user manual and run the Accumulo example code. Feel free to contact us if you have any questions. Accumulo has a programming mechanism (called Iterators) that can modify key/value pairs at various points in the data management process. Every Accumulo key/value pair has its own security label which limits query results based off user authorizations. Accumulo runs on a cluster using one or more HDFS instances. Nodes can be added or removed as the amount of data stored in Accumulo changes.

About

​Apache Spark's MLlib is a scalable machine learning library that integrates seamlessly with Spark's APIs, supporting Java, Scala, Python, and R. It offers a comprehensive suite of algorithms and utilities, including classification, regression, clustering, collaborative filtering, and tools for constructing machine learning pipelines. MLlib's high-quality algorithms leverage Spark's iterative computation capabilities, delivering performance up to 100 times faster than traditional MapReduce implementations. It is designed to operate across diverse environments, running on Hadoop, Apache Mesos, Kubernetes, standalone clusters, or in the cloud, and accessing various data sources such as HDFS, HBase, and local files. This flexibility makes MLlib a robust solution for scalable and efficient machine learning tasks within the Apache Spark ecosystem. ​

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Distributed key-value storage for companies in need of a robust, scalable data storage and retrieval solution

Audience

Data scientists and engineers wanting a machine learning solution for efficient data processing and analysis within the Apache Spark framework

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Apache Corporation
Founded: 1954
United States
accumulo.apache.org

Company Information

Apache Software Foundation
Founded: 1995
United States
spark.apache.org/mllib/

Alternatives

Apache HBase

Apache HBase

The Apache Software Foundation

Alternatives

Apache Spark

Apache Spark

Apache Software Foundation
HerdDB

HerdDB

Diennea
Apache Mahout

Apache Mahout

Apache Software Foundation
GridGain

GridGain

GridGain Systems
Amazon EMR

Amazon EMR

Amazon

Categories

Categories

Integrations

Amazon EC2
Apache Cassandra
Apache HBase
Apache Hive
Apache Mesos
Apache Spark
Apache ZooKeeper
Hadoop
Java
Kubernetes
MapReduce
Python
R
Scala

Integrations

Amazon EC2
Apache Cassandra
Apache HBase
Apache Hive
Apache Mesos
Apache Spark
Apache ZooKeeper
Hadoop
Java
Kubernetes
MapReduce
Python
R
Scala
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