1 repo
Systems for partitioning, transforming, and processing large-scale datasets across distributed computing clusters.
Distinguishing note: Specifically targets lazy, partitioned data processing rather than general database management or storage.
Explore 1 awesome GitHub repository matching data & databases · Distributed Data Processing Frameworks. Refine with filters or upvote what's useful.
Ray is a distributed computing framework designed to scale Python and Java applications across clusters by abstracting task scheduling and resource management. It functions as a resource-aware execution engine that manages task dependencies, placement, and fault tolerance across networked compute nodes. At its core, the system provides a stateful actor model, allowing developers to define classes that run in dedicated processes to maintain and mutate internal state across remote method calls. The framework distinguishes itself through a robust cross-language interoperability layer, enabling f
A framework that represents data as partitioned blocks to support incremental transformations and parallel execution across large clusters.