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flink

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About flink

Apache Flink is a data processing software from Apache that specializes in stateful computations over data streams. It offers architecture, applications, and operations, so users can efficiently process real-time data with complex event processing capabilities. Flink supports various use cases such as stream analytics and batch processing, allowing for versatile data management solutions. It is designed to handle large-scale distributed data processing with fault tolerance and high availability. Key capabilities: stream processing batch processing event time processing state management fault tolerance Best for: data engineers and developers that need to build and manage real-time data applications.

flink Details

Vendor
Apache
Year Launched
Location
Berlin, Germany
Deployment
Training Options
demo, account manager, community
Countries Served
All Countries
Languages
Budgeting, Business Intelligence, Business Performance Management, Dashboard, Financial Reporting, Reporting, Resource Management, Predictive Analytics, Project Planning, Project Tracking
Users
Budget Analysts, Data Analysts, Managers, Executives, Project Managers, Team Leaders, Financial Analysts, Business Intelligence Specialists, Resource Managers, Data Scientists.
Industries Served
Finance, Retail, Healthcare, Education, Technology, Manufacturing, Government, Non-Profit, Construction, Energy
Tags
Budgeting, Business Intelligence, Business Performance Management, Dashboard, Financial Reporting, Reporting, Resource Management, Predictive Analytics, Project Planning, Project Tracking.

flink's In-App Market Place

Does flink have an in-app market place?

Yes

How many Mini-Apps in the marketplace?

6

Mini Apps

1. FlinkML: A machine learning library for Flink that allows users to perform predictive analytics and build machine learning models.

2. Flink Gelly: A graph processing library for Flink that enables users to perform graph analytics and process large-scale graph data efficiently.

3. Flink SQL: Allows users to run SQL queries on Flink streams and tables

making it easier to process and analyze streaming data.

4. FlinkCEP: Complex Event Processing library for Flink that enables users to detect patterns and trends in real-time data streams.

5. FlinkMLLib: An extension to FlinkML that provides additional machine learning algorithms and functions for data analysis and modeling.

Pricing Options

Free trial
Free version
Request a quote
Promo Offer

Accepted Payment Currencies

USD ($), EUR (€), GBP (£), JPY (¥), AUD (A$), CAD (C$), CHF (CHF), CNY (CN¥), SEK (kr), NZD (NZ$).

Pros & Cons

  • High scalability and fault tolerance for handling large datasets
  • Real-time stream processing capabilities
  • Support for complex event processing and analytics
  • Integration with various data sources and tools
  • Efficient batch processing for analyzing historical data
  • Easy deployment and management in a distributed computing environment
  • Advanced APIs and libraries for building custom applications
  • Support for machine learning and predictive analytics
  • Comprehensive project planning and tracking features
  • Interactive dashboards for visualizing key performance indicators
  • Steep learning curve for beginners
  • Limited integration capabilities with other software
  • Lack of advanced visualization options
  • Issues with scalability for large datasets
  • High system resource requirements
  • Limited customer support options
  • Lack of detailed documentation for troubleshooting issues
  • Potential security vulnerabilities and concerns as an open-source software.

flink's Support Options

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