Apache Ambari and Bigtop are two separate projects in the big data ecosystem, and they play different roles in managing and deploying big data clusters. Let’s look at each of them:

1. Apache Ambari:

   • Apache Ambari is an open-source management and monitoring tool for big data clusters. It simplifies the provisioning, management, and monitoring of Hadoop clusters and other related big data technologies.
   • Ambari provides a web-based user interface for cluster administrators to set up and configure various components of a big data stack, such as Hadoop, Hive, HBase, Spark, and more.
   • It offers centralized management features, including automatic service start/stop, configuration management, and health checks for cluster components.
   • Ambari also includes monitoring and alerting capabilities, allowing administrators to track the health and performance of the cluster.

2. Bigtop:

   • Apache Bigtop is an open-source project focused on creating a comprehensive and community-driven packaging and testing framework for big data and data engineering components.
   • Bigtop aims to provide a standardized and repeatable way to build, package, and deploy big data software, including Hadoop, Spark, Hive, HBase, and others.
   • It ensures that the software components are built from source code, packaged into standard Linux packages (e.g., RPM or DEB), and tested for compatibility and correctness.
   • Bigtop supports various Linux distributions, making it easier to deploy big data stacks on different platforms.

Integration of Ambari and Bigtop:

• Apache Ambari and Bigtop can be used together to manage and deploy big data clusters.
• Ambari can use Bigtop’s standardized packages for deploying and managing the various components of a big data stack.
• Bigtop’s packaging and testing framework can help ensure that the software components deployed through Ambari are built and tested consistently.