Hadoop vs Cassandra: Unlock the Value of Your Data with Right Tool

Hadoop and Cassandra are both open-source software platforms that are designed to store and process large amounts of data. However, they are designed for different purposes and have different characteristics.

Hadoop is a framework for storing and processing large amounts of data distributed across a cluster of computers. 

The system is built to scale up from a large number of single servers to thousands of devices, each of which provides local computing and storage. Hadoop is based on the MapReduce programming model, which allows developers to write programs that can process vast amounts of data in parallel across the cluster. Hadoop is often used for batch processing and data warehousing applications, and is well-suited for tasks that involve large amounts of data that can be processed in parallel.

While offering high availability and no single point of failure, Cassandra is a distributed database management system that is built to handle enormous volumes of data across many commodity computers. Cassandra is particularly well-suited for handling large amounts of data with high write and read throughput, and is often used for real-time data processing applications such as online transaction processing, Internet of Things (IoT) applications, and user activity tracking.

In summary, Hadoop is a framework for storing and processing large amounts of data in parallel across a cluster of computers, while Cassandra is a distributed database management system designed for high availability and high write and read throughput. Both Hadoop and Cassandra are useful tools for handling large amounts of data, but they are designed for different purposes and have different characteristics.

The Apache Software Foundation family includes both Apache Cassandra and Apache Hadoop. We could have compared these two frameworks, but it wouldn’t be fair because Apache Hadoop is an ecosystem that includes a number of different parts. Big data storage is handled by Cassandra, thus we’ve chosen its counterpart from the Hadoop ecosystem, which is Hadoop Distributed File System (HDFS).