Running Distributed Computing Jobs with MongoDB Data

MongoDB

MongoDB is a source-available cross-platform document-oriented database program. Classified as a NoSQL database program, MongoDB uses JSON-like documents with optional schemas. MongoDB has become one of the most wanted databases in the world because it makes it easy for developers to store, manage, and retrieve data when creating applications with most programming languages. MongoDB is popular because it's easy to learn and get started. It's highly scalable (auto-sharding) and cost-effective, and it has a flexible data model.

Distributed Computing

Distributed computing technology refers to a system where multiple computers work together to solve a problem. It allows for parallel processing of data across multiple machines, which can lead to faster processing times. Distributed computing technology has become increasingly popular due to the rise of big data. It allows for the processing of large amounts of data that would be too large for a single machine to handle. Some examples of distributed computing technologies include Apache Hadoop, Apache Spark, and Apache Flink.

With the growing popularity of both MongoDB for data storage and distributed computing for compute workloads, it is unsurprising that many organizations are seeking to run distributed computing jobs with MongoDB data. Kaspian offers a native connector for this operation. Just register your MongoDB datastore and link your Distributed Computing job; Kaspian's autoscaling compute layer makes it easy to crunch through any data in your cloud with minimal setup or management.

Learn more about Kaspian and see how our flexible compute layer for the modern data cloud is already reshaping the way companies in industries like retail, manufacturing and logistics are thinking about data engineering and analytics.