Azure DatabricksMicrosoft
|
MLlibApache Software Foundation
|
|||||
Related Products
|
||||||
About
Unlock insights from all your data and build artificial intelligence (AI) solutions with Azure Databricks, set up your Apache Spark™ environment in minutes, autoscale, and collaborate on shared projects in an interactive workspace. Azure Databricks supports Python, Scala, R, Java, and SQL, as well as data science frameworks and libraries including TensorFlow, PyTorch, and scikit-learn. Azure Databricks provides the latest versions of Apache Spark and allows you to seamlessly integrate with open source libraries. Spin up clusters and build quickly in a fully managed Apache Spark environment with the global scale and availability of Azure. Clusters are set up, configured, and fine-tuned to ensure reliability and performance without the need for monitoring. Take advantage of autoscaling and auto-termination to improve total cost of ownership (TCO).
|
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
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
|
Platforms Supported
Windows
Not Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
|
|||||
Audience
Companies in need of a big data 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
Supported
24/7 Live Support
Not Supported
Online
Supported
|
Support
Phone Support
Supported
24/7 Live Support
Not Supported
Online
Supported
|
|||||
API
Offers API
Not Supported
|
API
Offers API
Supported
|
|||||
Screenshots and Videos |
Screenshots and Videos |
|||||
Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
|
Pricing
No information available.
Free Version
Not Supported
Free Trial
Not Supported
|
|||||
Reviews/
|
Reviews/
|
|||||
Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
|
Training
Documentation
Supported
Webinars
Supported
Live Online
Not Supported
In Person
Supported
|
|||||
Company InformationMicrosoft
Founded: 1975
United States
azure.microsoft.com/en-us/services/databricks/
|
Company InformationApache Software Foundation
Founded: 1995
United States
spark.apache.org/mllib/
|
|||||
Alternatives |
Alternatives |
|||||
|
|
|
|||||
|
|
||||||
|
|
||||||
|
|
||||||
Categories |
Categories |
|||||
Integrations
Ango Hub
Supported
Apache HBase
Not Supported
Artie
Supported
Azure Data Lake
Supported
Captain Compliance
Supported
DQOps
Supported
Dagster
Supported
Dasera
Supported
Databricks
Supported
Datagaps ETL Validator
Supported
|
Integrations
Ango Hub
Not Supported
Apache HBase
Supported
Artie
Not Supported
Azure Data Lake
Not Supported
Captain Compliance
Not Supported
DQOps
Not Supported
Dagster
Not Supported
Dasera
Not Supported
Databricks
Not Supported
Datagaps ETL Validator
Not Supported
|
|||||
|
|
|