13 Most Popular Big Data Analytics Tool

Apache Hadoop: An open-source, Java-based framework that allows for the distributed processing of large datasets across clusters of computers using simple programming models. It is the foundation of many other big data tools and technologie

Apache Spark: An open-source unified analytics engine for large-scale data processing. Spark offers faster processing than Hadoop MapReduce for a wide range of workload

Apache Kafka: An open-source platform for handling real-time data feeds. Kafka can be used to publish, subscribe to, and store streams of data, making it a popular choice for building real-time data pipeline

Apache Cassandra: An open-source, NoSQL distributed database management system designed to handle large amounts of data across many commodity servers. Cassandra is known for its high availability, scalability, and fault tolerance

Amazon Redshift: A cloud-based data warehouse service from Amazon Web Services (AWS) that is specifically designed for large datasets. Redshift is a popular choice for organizations that need to store and analyze large amounts of data in the cloud

Google Cloud Dataproc: A managed Hadoop and Spark service from Google Cloud Platform (GCP) that allows you to run Hadoop and Spark clusters on GCP. Dataproc is a good choice for organizations that are already using GCP for other cloud service

IBM Cloud Big Data: A suite of big data services from IBM Cloud that includes a variety of tools and technologies for big data analytics, such as Hadoop, Spark, and Cassandra. IBM Cloud Big Data is a good option for organizations that are looking for a comprehensive big data solution from a single vendor