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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 DataOps DataFlow?

Apache Spark offers a comprehensive component-driven platform that streamlines the automation of Data Reconciliation testing for contemporary Data Lake and Cloud Data Migration initiatives. DataOps DataFlow serves as an innovative web-based tool designed to facilitate the automation of testing for ETL projects, Data Warehouses, and Data Migrations. You can utilize DataFlow to efficiently load data from diverse sources, perform comparisons, and transfer discrepancies either into S3 or a Database. This enables users to create and execute data flows with remarkable ease. It stands out as a premier testing solution specifically tailored for Big Data Testing. Moreover, DataOps DataFlow seamlessly integrates with a wide array of both traditional and cutting-edge data sources, encompassing RDBMS, NoSQL databases, as well as cloud-based and file-based systems, ensuring versatility in data handling.

Media

Media

Integrations Supported

Amazon Redshift
Azure Synapse Analytics
Datagaps DataOps Suite
Microsoft Power BI
Red Hat Enterprise Linux
Snowflake
Tableau

Integrations Supported

Amazon Redshift
Azure Synapse Analytics
Datagaps DataOps Suite
Microsoft Power BI
Red Hat Enterprise Linux
Snowflake
Tableau

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Contact us
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site 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

Datagaps

Date Founded

2010

Company Location

United States

Company Website

www.datagaps.com/dataops-dataflow/

Categories and Features

DevOps

Approval Workflow
Dashboard
KPIs
Policy Management
Portfolio Management
Prioritization
Release Management
Timeline Management
Troubleshooting Reports

Categories and Features

Data Management

Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge

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