RethinkDB

RethinkDB
Name	RethinkDB
Developer	RethinkDB, Inc.
Released	2010
Latest release	2.4.0
Programming language	C++11, Python, JavaScript
Operating system	Linux, macOS, FreeBSD
License	Apache License 2.0

RethinkDB is an open-source distributed document-oriented database designed for real-time applications and push-based architectures. It was created to support interactive web applications and mobile backends with live changefeeds and JSON storage and was influenced by developments in modern web platforms and cloud infrastructure. The project intersects with several major companies and institutions in the technology industry and has been discussed alongside prominent software projects and events.

History

RethinkDB began as a startup effort involving contributors linked to universities and technology firms and launched during the era of increased interest in NoSQL solutions alongside projects such as MongoDB, Cassandra (database), CouchDB, Redis, and HBase. Early funding and attention connected it to accelerator programs and venture events similar to Y Combinator, TechCrunch Disrupt, and incubators in the Silicon Valley ecosystem. The project evolved in parallel with discussions at conferences like Strata (conference), Velocity (conference), and meetings featuring speakers from Google, Facebook, Amazon Web Services, and Microsoft. After initial commercial efforts, stewardship shifted to open source contributors resembling transitions experienced by projects such as OpenStack, Elastic NV, and Chef (software).

Architecture and Features

RethinkDB's architecture implements a distributed document store with JSON documents, secondary indexes, and a storage engine influenced by work from systems such as LevelDB, RocksDB, Berkeley DB, LMDB, and WiredTiger. It supports replication, clustering, and automatic failover comparable to designs from etcd, Zookeeper, Consul (software), and Raft (computer science). Key features include changefeeds for real-time push notifications, a query planner and execution engine analogous in role to components in PostgreSQL, MySQL, SQLite, and Oracle Database (product), and a web administration UI similar to tools from Kibana, Grafana, and pgAdmin. Storage and consistency trade-offs echo debates involving CAP theorem thinkers and systems research at institutions like MIT, Stanford University, UC Berkeley, and Carnegie Mellon University.

Query Language and Drivers

RethinkDB exposes a functional query language available through official drivers for languages reflecting ecosystems including Python (programming language), JavaScript, Ruby (programming language), Java (programming language), Go (programming language), and Clojure. The client-server protocol and driver ecosystem paralleled efforts in projects such as gRPC, Thrift, WebSocket, and RESTful APIs promoted by companies like Twitter, Netflix, LinkedIn, and GitHub. The query model supports chaining and transformation operations with semantics that were often compared to query features in SQL, LINQ, XPath, and functional languages taught at institutions such as Princeton University and Harvard University.

Performance and Scalability

RethinkDB's performance characteristics were evaluated against benchmarks involving throughput and latency alongside systems like MongoDB, Cassandra (database), Redis, and Elasticsearch. Its clustering and sharding strategies invoked research from distributed systems pioneers affiliated with Google, Amazon, Microsoft Research, and academia including UC Berkeley and MIT CSAIL. Performance tuning often referenced operating system and kernel developments in Linux, FreeBSD, and interactions with container platforms such as Docker, orchestration systems like Kubernetes, and cloud services from Amazon Web Services, Google Cloud Platform, and Microsoft Azure. Real-world scalability reports were shared at conferences including USENIX, ACM SIGMOD, and VLDB.

Use Cases and Adoption

Adoption scenarios for RethinkDB spanned real-time dashboards, collaborative editing, multiplayer game backends, and streaming analytics, paralleling usage patterns of technologies employed by Slack, Trello, Spotify, Uber, and Airbnb. Integrations were explored with messaging and streaming platforms such as Apache Kafka, RabbitMQ, and Apache Flink, and with frontend frameworks including React (JavaScript library), AngularJS, Vue.js, and Ember.js. Organizations in media, advertising, finance, and academia experimented with it alongside stacks featuring Node.js, Django, Ruby on Rails, and Spring Framework.

Development and Community

Development of RethinkDB involved a combination of corporate engineering teams, independent contributors, and academic collaborators, similar to community models seen in Linux kernel development, Apache Software Foundation projects, and Mozilla initiatives. The community communicated via channels such as mailing lists, chat platforms resembling Slack, and code hosting and review on platforms similar to GitHub and GitLab. Documentation and educational resources were produced by contributors in formats found at O'Reilly Media, university coursework, and conference tutorials at venues like PyCon, JSConf, and GopherCon.

Category:Distributed databases