JavaScript vs. MLlib vs. OCaml vs. TaffyDB Comparison Chart

​Apache Spark's MLlib is a scalable machine learning library that integrates seamlessly with Spark's APIs, supporting Java, Scala, Python, and R. It offers a comprehensive suite of algorithms and utilities, including classification, regression, clustering, collaborative filtering, and tools for constructing machine learning pipelines. MLlib's high-quality algorithms leverage Spark's iterative computation capabilities, delivering performance up to 100 times faster than traditional MapReduce implementations. It is designed to operate across diverse environments, running on Hadoop, Apache Mesos, Kubernetes, standalone clusters, or in the cloud, and accessing various data sources such as HDFS, HBase, and local files. This flexibility makes MLlib a robust solution for scalable and efficient machine learning tasks within the Apache Spark ecosystem. ​

​TaffyDB is an open source JavaScript library that brings powerful database functionality into your JavaScript applications. It offers a small file size with extremely fast queries and a powerful JavaScript-centric data selection engine. TaffyDB includes database-inspired features such as count, update, and insert, and provides robust cross-browser support. It is easily extended with your own functions and is compatible with any DOM library, as well as server-side JavaScript. Creating a database is straightforward, you can create a new empty database, a database with a single object, an array, or a JSON string. Once you have a database, you can run queries against it by calling the root function and building filter objects. TaffyDB allows you to filter using the database name and object comparison, access data easily, and modify data on the fly. You can also use functions to give you full control over the results of your query.