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Apache Hadoop

Analyze, store, and process large and diverse data sets efficiently and reliably.

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What is Apache Hadoop?

Apache Hadoop is an open-source framework designed to process and store extremely large datasets across clusters of computers. It works by breaking down data processing tasks into smaller pieces and distributing them across multiple machines, then combining the results. Hadoop is built to handle data that doesn't fit neatly into traditional databases and can work with unstructured information like text, images, and sensor data. It's particularly useful for organisations that need to analyse massive volumes of information without investing in expensive, single-machine solutions.

Key features

Distributed file system (HDFS)

stores large files across multiple computers while maintaining reliability through data replication

MapReduce processing

breaks complex data analysis jobs into smaller tasks that run in parallel across your cluster

Horizontal scalability

add more machines to handle growing data volumes without redesigning your system

Fault tolerance

automatically handles machine failures by replicating data and rerunning failed tasks

Works with diverse data types

processes structured, semi-structured, and unstructured data without rigid schema requirements

Pros & cons

Advantages

  • Completely free and open-source; no licensing costs regardless of scale
  • Can handle petabyte-scale datasets cost-effectively using ordinary hardware
  • Strong community support with extensive documentation and many related tools
  • Proven track record at major technology companies dealing with massive data volumes

Limitations

  • Steep learning curve; requires understanding of distributed systems concepts and Java programming
  • Slower than traditional databases for queries requiring quick results; better suited for batch processing than real-time analytics
  • Requires significant infrastructure investment and operational expertise to set up and maintain properly

Use cases

Processing web server logs to understand user behaviour patterns across millions of requests

Analysing scientific research data from thousands of sensors or instruments

Building recommendation systems that need to process user interaction data at massive scale

Data warehousing for organisations generating terabytes of information daily

Machine learning on large datasets where training data is too big for single machines

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Pricing

Free

Free

Full access to Apache Hadoop framework, HDFS, and MapReduce. No restrictions on usage or data volume.

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Try Apache Hadoop free
  • Free plan available
  • No credit card