A high-performance MongoDB client for R, built on libmongoc and jsonlite, supporting aggregation, indexing, and streaming.
mongolite is an R package that serves as a high-performance client for MongoDB databases. It allows R users to connect to MongoDB, perform queries, insert data, and execute advanced operations like aggregation and map-reduce directly from R scripts. The package solves the problem of integrating MongoDB's flexible document storage with R's data analysis capabilities, enabling seamless data workflows.
R developers, data scientists, and analysts who need to interact with MongoDB databases for data storage, retrieval, and analysis within R environments.
Developers choose mongolite for its speed, simplicity, and full feature set—it leverages the libmongoc driver for performance and provides a clean R API without sacrificing advanced MongoDB functionality like SSL encryption and streaming.
Fast and Simple MongoDB Client for R
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
Built on the libmongoc C driver, it ensures efficient data handling and low latency, as highlighted in the key features for fast MongoDB operations.
Integrates with jsonlite for automatic conversion between R objects and MongoDB documents, simplifying data import/export workflows, as shown in streaming examples.
Supports advanced operations like aggregation pipelines, indexing, and map-reduce, enabling full MongoDB functionality within R, per the documentation.
Includes SSL encryption and SASL authentication for secure connections, ensuring data protection in production environments, as noted in the features.
Limited to the R ecosystem, making it unsuitable for projects that involve other programming languages or require polyglot database access.
Installation on Linux requires manual installation of libssl-dev and libsasl2-dev, which can be a barrier for users without admin access or in containerized environments.
Lacks graphical interfaces for database management, requiring users to rely on command-line operations or external tools for visual data exploration.