Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

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.

Description

The Stackable data platform was crafted with a focus on flexibility and openness. It offers a carefully selected range of top-notch open source data applications, including Apache Kafka, OpenSearch, Trino, and Apache Spark. Unlike many competitors that either promote their proprietary solutions or enhance vendor dependence, Stackable embraces a more innovative strategy. All data applications are designed to integrate effortlessly and can be added or removed with remarkable speed. Built on Kubernetes, it is capable of operating in any environment, whether on-premises or in the cloud. To initiate your first Stackable data platform, all you require is stackablectl along with a Kubernetes cluster. In just a few minutes, you will be poised to begin working with your data. You can set up your one-line startup command right here. Much like kubectl, stackablectl is tailored for seamless interaction with the Stackable Data Platform. Utilize this command line tool for deploying and managing stackable data applications on Kubernetes. With stackablectl, you have the ability to create, delete, and update components efficiently, ensuring a smooth operational experience for your data management needs. The versatility and ease of use make it an excellent choice for developers and data engineers alike.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Apache HBase Yes 
Apache Hive Yes 
Apache Spark Yes 
Kubernetes Yes 
Amazon EC2 Yes 
Apache Airflow No 
Apache Druid No 
Apache Iceberg No 
Apache NiFi No 
Apache ZooKeeper No 
Git No 
Hadoop Yes 
Java Yes 
MapReduce Yes 
MinIO No 
OpenSearch No 
Prometheus No 
Python Yes 
Scala Yes 
Trino No 

Integrations

Apache HBase Yes 
Apache Hive Yes 
Apache Spark Yes 
Kubernetes Yes 
Amazon EC2 No 
Apache Airflow Yes 
Apache Druid Yes 
Apache Iceberg Yes 
Apache NiFi Yes 
Apache ZooKeeper Yes 
Git Yes 
Hadoop No 
Java No 
MapReduce No 
MinIO Yes 
OpenSearch Yes 
Prometheus Yes 
Python No 
Scala No 
Trino Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

Free
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 Yes 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

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

Customer Support

Business Hours Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Types of Training

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

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Vendor Details

Company Name

Apache Software Foundation

Founded

1995

Country

United States

Website

spark.apache.org/mllib/

Vendor Details

Company Name

Stackable

Founded

2020

Country

Germany

Website

stackable.tech/

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 

Product Features

Data Management

Customer Data No 
Data Analysis No 
Data Capture No 
Data Integration No 
Data Migration Yes 
Data Quality Control No 
Data Security Yes 
Information Governance No 
Master Data Management No 
Match & Merge No 

Data Warehouse

Ad hoc Query No 
Analytics Yes 
Data Integration Yes 
Data Migration Yes 
Data Quality Control No 
ETL - Extract / Transfer / Load Yes 
In-Memory Processing No 
Match & Merge No 

Alternatives

Alternatives

Apache Spark Reviews

Apache Spark

Apache Software Foundation
Amazon EMR Reviews

Amazon EMR

Amazon
Hercules Reviews

Hercules

Leisure Holding
Apache Mahout Reviews

Apache Mahout

Apache Software Foundation
Canvas Credentials Reviews

Canvas Credentials

Instructure