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What is Cloudera Data Platform?

Utilize the strengths of both private and public cloud environments with a distinctive hybrid data platform designed for modern data frameworks, which facilitates data access from virtually anywhere. Cloudera distinguishes itself as a versatile hybrid data platform, providing unmatched flexibility that enables users to select any cloud service, any analytics tool, and any data type they require. It simplifies the processes of managing data and conducting analytics, ensuring top-notch performance, scalability, and security for data access across diverse locations. By adopting Cloudera, organizations can leverage the advantages of both private and public cloud infrastructures, resulting in rapid value creation and improved governance over IT assets. In addition, Cloudera allows users to securely move data, applications, and personnel back and forth between their data center and multiple cloud environments, regardless of where the data resides. This two-way functionality not only boosts operational efficiency but also cultivates a more flexible and responsive approach to data management. Ultimately, Cloudera equips organizations with the tools necessary to navigate the complexities of data in a connected world, enhancing their strategic decision-making capabilities.

What is Apache Spark?

Apache Spark™ is a powerful analytics platform crafted for large-scale data processing endeavors. It excels in both batch and streaming tasks by employing an advanced Directed Acyclic Graph (DAG) scheduler, a highly effective query optimizer, and a streamlined physical execution engine. With more than 80 high-level operators at its disposal, Spark greatly facilitates the creation of parallel applications. Users can engage with the framework through a variety of shells, including Scala, Python, R, and SQL. Spark also boasts a rich ecosystem of libraries—such as SQL and DataFrames, MLlib for machine learning, GraphX for graph analysis, and Spark Streaming for processing real-time data—which can be effortlessly woven together in a single application. This platform's versatility allows it to operate across different environments, including Hadoop, Apache Mesos, Kubernetes, standalone systems, or cloud platforms. Additionally, it can interface with numerous data sources, granting access to information stored in HDFS, Alluxio, Apache Cassandra, Apache HBase, Apache Hive, and many other systems, thereby offering the flexibility to accommodate a wide range of data processing requirements. Such a comprehensive array of functionalities makes Spark a vital resource for both data engineers and analysts, who rely on it for efficient data management and analysis. The combination of its capabilities ensures that users can tackle complex data challenges with greater ease and speed.

Media

Media

Integrations Supported

Apache Hive
Azure Marketplace
Hadoop
Progress DataDirect
Protegrity
Querona
doolytic
Value Innovation Labs Enterprise HRMS

Integrations Supported

Apache Hive
Azure Marketplace
Hadoop
Progress DataDirect
Protegrity
Querona
doolytic
Akira AI
Apache PredictionIO
Azure Data Science Virtual Machines
DataNimbus
Gemini Enterprise Agent Platform Notebooks
JanusGraph
JupyterLab
LogIsland
Retina
Speedb
Stackable
TIMi

API Availability

API Availability

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

Pricing not provided
Free Version

Supported Platforms

SaaS
Windows
Mac
On-Prem

Supported Platforms

SaaS

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Not specified

Training Options

Documentation Hub
Webinars
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

Cloudera

Date Founded

2008

Company Location

United States

Company Website

www.cloudera.com/products/cloudera-data-platform.html

Company Facts

Organization Name

Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

spark.apache.org

Categories and Features

Data Analysis

Data Discovery
Data Visualization

Data Management

Customer Data
Data Capture

Data Management Platforms (DMP)

Audience Targeting
Campaign Management
Customer Journey Mapping
Data Capture / Transfer
Data Visualization

Hybrid Cloud

Not specified

Categories and Features

Big Data

Not specified

Data Analysis

Not specified

Data Modeling

Not specified

Query Engines

Not specified

Streaming Analytics

Data Enrichment
Data Wrangling / Data Prep
Multiple Data Source Support
Process Automation

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