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Average Ratings 0 Ratings

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features
design
support

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Write a Review

Description

Azure Data Lake offers a comprehensive set of features designed to facilitate the storage of data in any form, size, and speed for developers, data scientists, and analysts alike, enabling a wide range of processing and analytics across various platforms and programming languages. By simplifying the ingestion and storage of data, it accelerates the process of launching batch, streaming, and interactive analytics. Additionally, Azure Data Lake is compatible with existing IT frameworks for identity, management, and security, which streamlines data management and governance. Its seamless integration with operational stores and data warehouses allows for the extension of current data applications without disruption. Leveraging insights gained from working with enterprise clients and managing some of the world's largest processing and analytics tasks for services such as Office 365, Xbox Live, Azure, Windows, Bing, and Skype, Azure Data Lake addresses many of the scalability and productivity hurdles that hinder your ability to fully utilize data. Ultimately, it empowers organizations to harness their data's potential more effectively and efficiently than ever before.

Description

PySpark serves as the Python interface for Apache Spark, enabling the development of Spark applications through Python APIs and offering an interactive shell for data analysis in a distributed setting. In addition to facilitating Python-based development, PySpark encompasses a wide range of Spark functionalities, including Spark SQL, DataFrame support, Streaming capabilities, MLlib for machine learning, and the core features of Spark itself. Spark SQL, a dedicated module within Spark, specializes in structured data processing and introduces a programming abstraction known as DataFrame, functioning also as a distributed SQL query engine. Leveraging the capabilities of Spark, the streaming component allows for the execution of advanced interactive and analytical applications that can process both real-time and historical data, while maintaining the inherent advantages of Spark, such as user-friendliness and robust fault tolerance. Furthermore, PySpark's integration with these features empowers users to handle complex data operations efficiently across various datasets.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Amazon SageMaker Data Wrangler No 
Apache Hudi Yes 
Apache Pinot Yes 
Apache Spark No 
Azure Databricks Yes 
Azure Synapse Analytics Yes 
Dasera Yes 
Gemini Enterprise Agent Platform Notebooks Yes 
Hyper Historian Yes 
Microsoft Fabric Yes 
Microsoft Power Query Yes 
Okera Yes 
Openbridge Yes 
Privacera Yes 
PubSub+ Platform Yes 
QuerySurge Yes 
SSIS Integration Toolkit Yes 
StarfishETL Yes 
Validio Yes 
Visual Studio Yes 

Integrations

Amazon SageMaker Data Wrangler Yes 
Apache Hudi No 
Apache Pinot No 
Apache Spark Yes 
Azure Databricks No 
Azure Synapse Analytics No 
Dasera No 
Gemini Enterprise Agent Platform Notebooks No 
Hyper Historian No 
Microsoft Fabric No 
Microsoft Power Query No 
Okera No 
Openbridge No 
Privacera No 
PubSub+ Platform No 
QuerySurge No 
SSIS Integration Toolkit No 
StarfishETL No 
Validio No 
Visual Studio 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 No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
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 Yes 
Live Rep (24/7) Yes 
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 No 

Types of Training

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

Vendor Details

Company Name

Microsoft

Founded

1975

Country

United States

Website

azure.microsoft.com/en-us/solutions/data-lake/

Vendor Details

Company Name

PySpark

Website

spark.apache.org/docs/latest/api/python/

Product Features

Product Features

Application Development

Access Controls/Permissions No 
Code Assistance No 
Code Refactoring No 
Collaboration Tools No 
Compatibility Testing No 
Data Modeling No 
Debugging No 
Deployment Management No 
Graphical User Interface No 
Mobile Development No 
No-Code No 
Reporting/Analytics No 
Software Development No 
Source Control No 
Testing Management No 
Version Control No 
Web App Development No 

Alternatives

Alternatives

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Apache Spark

Apache Software Foundation
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OneBlox

StorageCraft
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Spark Streaming

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