Discover the growing power of open source in big data! This guide explores how CTOs and SREs can use open source big data tools like Hadoop, Spark, and Kafka to build scalable, powerful, and cost-effective data platforms. Learn about the benefits, challenges, and best practices for adopting open source in your big data strategy.

With more focus on big data and the need to translate many data sources to other data consumers, Apache Kafka has emerged as the leading tool for efficiently and reliably handling this. In addition to configurations, maximizing Kafka’s capabilities is tied directly to the infrastructure you select.

What Is ClickHouse?

ClickHouse is an open source columnar database management system created by Yandex in 2016. ClickHouse was designed to provide users with a rapid and efficient system for processing large-scale analytical queries on enormous  volumes of data. Today, organizations use ClickHouse for data warehousing, business intelligence, and analytical processing.

Dedicated Servers for Apache Spark

In the landscape of big data analytics, Apache Spark has emerged as a powerful tool for in memory big data processing. The foundation for maximizing Spark’s capabilities lies in the infrastructure. OpenMetal’s XL V2.1 servers offer a solution that marries high performance with cost-effectiveness for Spark clusters.