Apache Hadoop

Apache Hadoop is primarily used for storing and processing large volumes of data in a distributed environment.

Yes, Apache Hadoop is open-source software with a freemium model, offering both free and enterprise versions.

Apache Hadoop can be set up locally, but it requires significant resources and configuration for optimal performance.

Apache Hadoop is the foundational framework that launched the big data era. It provides a distributed file system (HDFS) and a processing model (MapReduce) that allow for the storage and processing of massive datasets across clusters of commodity hardware. While modern cloud-native tools have largely replaced MapReduce and HDFS for most use cases, Hadoop remains a significant part of the big data landscape, particularly in on-premises environments. It serves as the base for many other big data tools, including Hive, HBase, and Spark, which have evolved to provide better performance and usability.

Apache Hadoop scores 7.5/10 (Good) on Lunoo, making it a well-rated option in the Data Science category. Apache Hadoop scores 9.2/10 due to its robust scalability, fault tolerance, and support for distributed storage and parallel computing. However, it fa...

Free Plan. Visit the official website for the most up-to-date pricing.

See our alternatives page for Apache Hadoop for a ranked list with scores. Top alternatives include: Google Colab, The Printing Press, Ursula K. Le Guin.

Ideal for enterprises and large organizations needing scalable data processing solutions.

See our detailed comparison of Apache Hadoop vs Google Colab with scores, features, and an AI-powered verdict.

With a score of 7.5/10, Apache Hadoop is a solid option in Data Science. See all Data Science ranked.

• API: Provides REST API for integration with other applications
• Platform: Cross-platform
• Integration: Supports various data sources and storage systems
• Programming Languages: Java, Python