Apache Spark is a unified engine for large-scale data processing and analytics.
Open source
24 alternativesHadoop
Framework that allows for the distributed processing of large data sets across clusters.
About Hadoop
Apache Hadoop is a software library for distributed processing of large data sets across clusters of computers using simple programming models. It includes components for storage, scheduling, and processing and is designed to scale from single servers to thousands of machines, each providing local computation and storage.
The library is designed to detect and handle failures at the application layer rather than depend on hardware for availability. Some releases require separate setup for external services, such as downloading the AWS SDK bundle to use the S3A connector.
Key features
- Distributed processing of large data sets using simple programming models
- Scales from single servers to thousands of machines with local storage
- Detects and handles failures at the application layer
- HDFS provides high-throughput access to application data
- YARN for job scheduling and cluster resource management
- MapReduce for parallel processing of large data sets
Best for: Organizations and researchers that need to process large data sets across computer clusters for production or research use.
Good for
- Scales from single servers to thousands of machines with local computation and storage
- Detects and handles failures at the application layer instead of relying on hardware
- Provides separate modules for file storage, resource management, and parallel processing
Watch out for
- Release 3.4.3 does not include the AWS SDK bundle needed for the S3A connector
Hadoop at a glance
- Website
- hadoop.apache.org
- Category
- AI & Machine Learning › AI Data & Analytics
- Type
- Online tool
- Pricing
- Not confirmed. Check the site
- Platforms
- Web
- Open source
- Not stated
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
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Hadoop FAQ
What modules does Hadoop include?
Hadoop Common for shared utilities, HDFS for distributed file storage, YARN for job scheduling and cluster resource management, and MapReduce for parallel processing of large data sets.
How does Hadoop handle computer failures?
The library is designed to detect and handle failures at the application layer, allowing service on top of a cluster where individual computers may fail.
How do I use the S3A connector with release 3.4.3?
Download version 2.35.4 of the AWS SDK bundle from Maven Central, verify its signature, and copy the JAR to share/hadoop/common/lib/.
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