- Apache Flink - Discussion
- Apache Flink - Useful Resources
- Apache Flink - Quick Guide
- Apache Flink - Conclusion
- Apache Flink - Flink vs Spark vs Hadoop
- Apache Flink - Use Cases
- Apache Flink - Machine Learning
- Apache Flink - Libraries
- Apache Flink - Running a Flink Program
- Creating a Flink Application
- Apache Flink - Table API and SQL
- Apache Flink - API Concepts
- Apache Flink - Setup/Installation
- Apache Flink - System Requirements
- Apache Flink - Architecture
- Apache Flink - Introduction
- Batch vs Real-time Processing
- Apache Flink - Big Data Platform
- Apache Flink - Home
Selected Reading
- Who is Who
- Computer Glossary
- HR Interview Questions
- Effective Resume Writing
- Questions and Answers
- UPSC IAS Exams Notes
Apache Fpnk - Conclusion
The comparison table that we saw in the previous chapter concludes the pointers pretty much. Apache Fpnk is the most suited framework for real-time processing and use cases. Its single engine system is unique which can process both batch and streaming data with different APIs pke Dataset and DataStream.
It does not mean Hadoop and Spark are out of the game, the selection of the most suited big data framework always depends and vary from use case to use case. There can be several use cases where a combination of Hadoop and Fpnk or Spark and Fpnk might be suited.
Nevertheless, Fpnk is the best framework for real time processing currently. The growth of Apache Fpnk has been amazing and the number of contributors to its community is growing day by day.
Happy Fpnking!
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