OPEN SOURCE SOFTWARE
Some of our products are available for anyone to use.
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LeoFS
LeoFS is a distributed object storage which offers highly available, distributed, eventually consistent storage system. It supports S3-API, multi data center replication, built-in cache mechanism and so on. It's possible to build in-house fast object storage instead of S3 and to deal with secure files. LeoFS can make a great contribution to reduce cost.
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Egison
Egison is the pattern-matching-oriented, pure functional programming language. Egison simplifies code by replacing complex nested loops and conditional branches with an intuitive pattern-matching expression. Egison is improving day by day. Recently, we added the facility to handle databases with intuitive Egison pattern-matching. We also released a Ruby extension for Egison pattern-matching.
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ROMA
ROMA is a distributed key-value store implemented by Ruby. It offers high availability and scalability with pure P2P architecture. The most significant feature of ROMA is flexibility to add customisable functions on ROMA developed by engineers. You can use not only simple strings but also lists on ROMA. Furthermore, the ROMA project also provides various clients for languages such as Ruby, PHP, and Java.
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Fairy
Fairy is a framework for distributed processing like MapReduce in Ruby. Fairy supports a programming model called filter IF, and various built-in filters. It offers high productivity and simplicity because of its API-like Ruby programming. It's expected to increase productivity.
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Rakuten MA
Rakuten MA is a morphological analyzer (word segmentor + PoS Tagger) for Chinese and Japanese written purely in JavaScript. It works on modern browsers and node.js, and implements incremental update of models by online machine learning. It also supports compact model representations and is bundled with Chinese and Japanese models trained from general corpora and e-commerce corpora.
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Category2Vec
Category2Vec is an implementation of the category vector models [Marui and Hagiwara 2015], and the paragraph vector models [Le and Mikolov 2014]. These programs are based on word2vec [Mikolov et al. 2013a,b] in gensim project [Rahurek 2013]. After training, you can obtain distributed representations for categories, paragraphs, and words. You can also infer a category from a description.
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RUM: Rakuten Unified Memory
Rakuten Unified Memory, or RUM, is a distributed in-memory data grid proof of concept. RUM enables vertical scaling for applications to as much RAM as is present on the machines in the network. RUM uses user-space networking to by-pass the kernel networking stack, and reduce latency. RUM includes examples for integration with existing application, a key value store, and a representative implementation of s3cmd, enabling RUM to be used as a simple but efficient filesystem.