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What is Maxeler Technologies?

Maxeler provides state-of-the-art dataflow solutions that integrate effortlessly into operational data centers, enabling easy programming and oversight. These high-performance systems are designed specifically for production server environments, ensuring they work harmoniously with popular operating systems and management tools. Our powerful management software efficiently handles resource distribution, scheduling, and data transfer within the dataflow computing architecture. Moreover, Maxeler dataflow nodes are compatible with standard Linux distributions, such as Red Hat Enterprise versions 4 and 5, without requiring any modifications. Any application intended for acceleration can operate on a Maxeler node as a typical Linux executable, simplifying the transition for developers. By incorporating the dataflow library into their existing code, developers can create new applications using straightforward function interfaces to harness its features. The MaxCompiler tool offers extensive debugging assistance during the development phase, including a high-speed simulator that enables code validation before deployment. This proactive approach ensures that developers can enhance their applications while reducing the chances of errors significantly. Furthermore, Maxeler’s dedication to continuous improvement ensures that users benefit from the most recent innovations in dataflow technology, keeping them at the forefront of the industry. Ultimately, this commitment to progress positions Maxeler as a leader in the realm of dataflow solutions, driving efficiency and performance for all users.

What is Cloudera DataFlow?

Cloudera DataFlow for the Public Cloud (CDF-PC) serves as a flexible, cloud-based solution for data distribution, leveraging Apache NiFi to help developers effortlessly connect with a variety of data sources that have different structures, process that information, and route it to many potential destinations. Designed with a flow-oriented low-code approach, this platform aligns well with developers’ preferences when they are crafting, developing, and testing their data distribution pipelines. CDF-PC includes a vast library featuring over 400 connectors and processors that support a wide range of hybrid cloud services, such as data lakes, lakehouses, cloud warehouses, and on-premises sources, ensuring a streamlined and adaptable data distribution process. In addition, the platform allows for version control of the data flows within a catalog, enabling operators to efficiently manage deployments across various runtimes, which significantly boosts operational efficiency while simplifying the deployment workflow. By facilitating effective data management, CDF-PC ultimately empowers organizations to drive innovation and maintain agility in their operations, allowing them to respond swiftly to market changes and evolving business needs. With its robust capabilities, CDF-PC stands out as an indispensable tool for modern data-driven enterprises.

Media

Media

Integrations Supported

Red Hat Enterprise Linux

Integrations Supported

Cloudera
Cloudera Data Platform
Litmus Edge
Talend Data Preparation
Ternary

API Availability

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

Not specified

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training

Company Facts

Organization Name

Maxeler Technologies

Date Founded

2003

Company Location

United Kingdom

Company Website

www.maxeler.com/products/software/

Company Facts

Organization Name

Cloudera

Date Founded

2008

Company Location

United States

Company Website

www.cloudera.com/products/cdf.html

Categories and Features

DevOps

Not specified

Categories and Features

Data Integration

Not specified

Streaming Analytics

Data Enrichment
Data Wrangling / Data Prep
Multiple Data Source Support
Process Automation
Real-time Analysis / Reporting
Visualization Dashboards

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