Ray is an open-source unified compute framework that makes it easy to scale AI and Python workloads — from reinforcement learning to deep learning to tuning, and model serving. Ray is a unified way to scale Python and AI applications from a single node to a cluster.
 
Ray AI Runtime (AIR) is an open-source toolkit for building ML applications. It provides libraries for distributed data processing, model training, tuning, reinforcement learning, model serving, and more.
 
Ray Core provides a simple and flexible API for building and running your distributed applications. You can often parallelize single machine code with little to zero code changes.
 
With a Ray cluster you can deploy your workloads on AWS, GCP, Azure or on premise. You can also use Ray cluster managers to run Ray on your existing Kubernetes, YARN, or Slurm clusters.

Ray is an open-source unified compute framework that makes it easy to scale AI and Python workloads — from reinforcement learning to deep learning to tuning, and model serving. Ray is a unified way to scale Python and AI applications from a single node to a cluster.


Ray - A unified framework for scaling AI and Python applications

Celery is an asynchronous task queue/job queue based on distributed message passing. It is focused on real-time operation, but supports scheduling as well. The execution units, called tasks, are executed concurrently on a single or more worker servers using multiprocessing, Eventlet, or gevent. Tasks can execute asynchronously (in the background) or synchronously (wait until ready).

Celery - Distributed Task Queue

Mercurial is a free, distributed source control management tool. It offers you the power to efficiently handle projects of any size while using an intuitive interface. It is easy to use and hard to break, making it ideal for anyone working with versioned files. Traditional version control systems such as Subversion are typical client-server architectures with a central server to store the revisions of a project. In contrast, Mercurial is truly distributed, giving each developer a local copy of the entire development history. This way it works independent of network access or a central server. Committing, branching and merging are fast and cheap. Mercurials implementation and data structures are designed to be fast. You can generate diffs between revisions, or jump back in time within seconds. Therefore Mercurial is perfectly suitable for large projects such as OpenJDK (hg) or NetBeans (hg).

Mercurial is fast and powerful. Mercurial offers you the power and speed to efficiently handle projects of any size and kind. Every clone contains the whole project history, so committing, branching, tagging and merging are local operations which makes them fast and convenient. You can use a multitude of workflows and easily enhance its functionality with extensions.

Mercurial

BigchainDB allows developers and enterprise to deploy blockchain proof-of-concepts, platforms and applications with a scalable blockchain database, supporting a wide range of industries and use cases. It is a decentralization ecosystem: a decentralized database, at scale. It can perform 1 million writes per second throughput, store petabytes of data, and sub-second latency.
 
The BigchainDB design starts with a distributed database (DB), and through a set of innovations adds blockchain characteristics: decentralized control, immutability, and creation & movement of digital assets. BigchainDB inherits characteristics of modern distributed databases: linear scaling in throughput and capacity with the number of nodes, a full-featured NoSQL query language, efficient querying, and permissioning. Being built on an existing distributed DB, it also inherits enterprise-hardened code for most of its codebase.

BigchainDB allows developers and enterprise to deploy blockchain proof-of-concepts, platforms and applications with a scalable blockchain database, supporting a wide range of industries and use cases.  It is a decentralization ecosystem: a decentralized database, at scale. It can perform 1 million writes per second throughput, store petabytes of data, and sub-second latency.

BigchainDB - The Scalable Blockchain Database

RhodeCode is an open source repository management platform. It provides unified security and team collaboration across Git, Subversion, and Mercurial. Pick the repository type depending on your project, not on your code management tool. Read and write in all repository types from one central point, and see commits, forks, and changeset merges at a glance. Its features include Intuitive System Management, Full text search, Access Management, Change log etc.

RHodeCode - Centralized control for distributed repositories

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Ray - A unified framework for scaling AI and Python applications

Celery - Distributed Task Queue

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BigchainDB - The Scalable Blockchain Database

RHodeCode - Centralized control for distributed repositories

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Ray - A unified framework for scaling AI and Python applications

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BigchainDB - The Scalable Blockchain Database

RHodeCode - Centralized control for distributed repositories

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