Apache Flink vs Pachyderm: What are the differences?
Developers describe Apache Flink as "Fast and reliable large-scale data processing engine". Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala. On the other hand, Pachyderm is detailed as "MapReduce without Hadoop. Analyze massive datasets with Docker". Pachyderm is an open source MapReduce engine that uses Docker containers for distributed computations.
Apache Flink and Pachyderm can be categorized as "Big Data" tools.
Some of the features offered by Apache Flink are:
- Hybrid batch/streaming runtime that supports batch processing and data streaming programs.
- Custom memory management to guarantee efficient, adaptive, and highly robust switching between in-memory and data processing out-of-core algorithms.
- Flexible and expressive windowing semantics for data stream programs
On the other hand, Pachyderm provides the following key features:
- Git-like File System
- Dockerized MapReduce
- Microservice Architecture
Apache Flink and Pachyderm are both open source tools. Apache Flink with 9.35K GitHub stars and 5K forks on GitHub appears to be more popular than Pachyderm with 3.81K GitHub stars and 369 GitHub forks.