Mercurial vs Storm
Overview
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Detailed Comparison
Mercurial is dedicated to speed and efficiency with a sane user interface. It is written in Python. Mercurial's implementation and data structures are designed to be fast. You can generate diffs between revisions, or jump back in time within seconds. | Apache Storm is a free and open source distributed realtime computation system. Storm makes it easy to reliably process unbounded streams of data, doing for realtime processing what Hadoop did for batch processing. Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more. Storm is fast: a benchmark clocked it at over a million tuples processed per second per node. It is scalable, fault-tolerant, guarantees your data will be processed, and is easy to set up and operate. |
| - | Storm integrates with the queueing and database technologies you already use;Simple API;Scalable;Fault tolerant;Guarantees data processing;Use with any language;Easy to deploy and operate;Free and open source |
Statistics | |
GitHub Stars - | GitHub Stars 6.7K |
GitHub Forks - | GitHub Forks 4.1K |
Stacks 229 | Stacks 208 |
Followers 219 | Followers 282 |
Votes 105 | Votes 25 |
Pros & Cons | |
Pros
Cons
| Pros
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Integrations | |
| No integrations available | |
What are some alternatives to Mercurial, Apache Storm?
Git
Git is a free and open source distributed version control system designed to handle everything from small to very large projects with speed and efficiency.
Apache NiFi
An easy to use, powerful, and reliable system to process and distribute data. It supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic.
SVN (Subversion)
Subversion exists to be universally recognized and adopted as an open-source, centralized version control system characterized by its reliability as a safe haven for valuable data; the simplicity of its model and usage; and its ability to support the needs of a wide variety of users and projects, from individuals to large-scale enterprise operations.
Plastic SCM
Plastic SCM is a distributed version control designed for big projects. It excels on branching and merging, graphical user interfaces, and can also deal with large files and even file-locking (great for game devs). It includes "semantic" features like refactor detection to ease diffing complex refactors.
Confluent
It is a data streaming platform based on Apache Kafka: a full-scale streaming platform, capable of not only publish-and-subscribe, but also the storage and processing of data within the stream
Pijul
Pijul is a free and open source (AGPL 3) distributed version control system. Its distinctive feature is to be based on a sound theory of patches, which makes it easy to learn and use, and really distributed.
KSQL
KSQL is an open source streaming SQL engine for Apache Kafka. It provides a simple and completely interactive SQL interface for stream processing on Kafka; no need to write code in a programming language such as Java or Python. KSQL is open-source (Apache 2.0 licensed), distributed, scalable, reliable, and real-time.
Heron
Heron is realtime analytics platform developed by Twitter. It is the direct successor of Apache Storm, built to be backwards compatible with Storm's topology API but with a wide array of architectural improvements.
DVC
It is an open-source Version Control System for data science and machine learning projects. It is designed to handle large files, data sets, machine learning models, and metrics as well as code.
Magit
It is an interface to the version control system Git, implemented as an Emacs package. It aspires to be a complete Git porcelain. While we cannot (yet) claim that it wraps and improves upon each and every Git command, it is complete enough to allow even experienced Git users to perform almost all of their daily version control tasks directly from within Emacs. While many fine Git clients exist, only deserve to be called porcelains.
