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Apache Hadoop HDFS

hadoop.apache.org

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Spec score 8.9 #1 of 19 in Data Lake Software

What it is

Apache Hadoop HDFS is a free, open-source distributed file system for high-throughput access to large application data sets on commodity hardware. It is designed for clusters of hundreds of nodes and can support tens of millions of files in one instance. HDFS copies file blocks across machines and detects failed DataNodes so it can start creating replacement copies. Its design prioritizes batch processing and streaming throughput rather than low-latency interactive workloads. Files follow a write-once, read-many model: appends and truncates are supported, but arbitrary in-place changes are not. Applications can connect through Java, a C wrapper, REST, a browser interface or an NFS gateway. The documentation lists connectors for Google Cloud Storage, Amazon S3, Azure Blob Storage and Azure Data Lake Storage. HDFS supports transparent encryption. Apache warns that without Kerberos caller authentication, anyone with network access to cluster servers can access data and run code, and recommends securing clusters before production. Apache also recommends checking release downloads with GPG signatures or SHA-512 checksums. The listed stable release is Hadoop 3.5.0, dated April 2, 2026.

Spec sheet

Purpose
HDFS is a distributed file system designed for high-throughput access to large application data sets on commodity hardware.Read 4 Oct 2026 · hadoop.apache.org
Integrations
Hadoop 3.5.0 includes a FileSystem implementation for Google Cloud Storage, and its documentation also lists connectors for Amazon S3, Azure Blob Storage, and Azure Data Lake Storage.Read 4 Oct 2026 · hadoop.apache.org
Security
Production clusters are expected to use Kerberos for caller authentication and access control.Read 15 Oct 2026 · hadoop.apache.org
Support
The project asks users not to request private support from its non-paid volunteers and directs help requests to module mailing lists.Read 4 Oct 2026 · hadoop.apache.org
License
Apache packages are generally distributed under the OSI-approved Apache License 2.0 unless a package states otherwise.Read 15 Oct 2026 · apache.org
Maker
The Apache Hadoop project is developed as open-source software by the Apache Software Foundation.Read 4 Oct 2026 · hadoop.apache.org
Architecture
A cluster uses a NameNode for namespace and access coordination and DataNodes for block storage and serving reads and writes.Read 15 Oct 2026 · hadoop.apache.org
Cloud integrations
The current documentation lists compatible file systems for Amazon S3, Azure Blob, Azure Data Lake, Google Cloud Storage, Aliyun OSS, Tencent COS, Huawei OBS and VolcanoEngine TOS.Read 15 Oct 2026 · hadoop.apache.org
Current release
Apache Hadoop 3.5.0 is the first stable release in the 3.5 line and adds full server-side Java 17 support.Read 15 Oct 2026 · hadoop.apache.org
Deployment modes
The setup guide covers standalone, pseudo-distributed, fully distributed and Docker-container operation.Read 15 Oct 2026 · hadoop.apache.org
Documentation breadth
The documentation set includes architecture, user guides, commands, Java API references, shell API, configuration references and security guides.Read 15 Oct 2026 · hadoop.apache.org
Encryption
HDFS documentation includes transparent encryption as a supported feature.Read 4 Oct 2026 · hadoop.apache.org
Erasure coding
The current documentation includes HDFS erasure-coding policies and operations.Read 15 Oct 2026 · hadoop.apache.org
Fault tolerance
HDFS is designed to tolerate hardware failures and uses replicated blocks across DataNodes.Read 15 Oct 2026 · hadoop.apache.org
Hadoop scope
Apache Hadoop provides open-source software for reliable, scalable distributed computing across clusters.Read 15 Oct 2026 · hadoop.apache.org
High availability
NameNode high availability can use shared NFS storage or a distributed Journal edit log, with the Journal approach recommended.Read 15 Oct 2026 · hadoop.apache.org
Interfaces
Applications can use the Java FileSystem API, a C wrapper, WebHDFS REST, browser access or the NFS gateway.Read 15 Oct 2026 · hadoop.apache.org
Large-file model
HDFS targets write-once-read-many workloads and commonly uses 128 MB blocks.Read 15 Oct 2026 · hadoop.apache.org
Legal and funding profile
Crunchbase identifies the legal name as The Apache Software Foundation, a U.S. nonprofit established in 1999 and funded by individual donations and corporate sponsors.Read 15 Oct 2026 · crunchbase.com
Limit: learning and integration
TrustRadius reviewers say the many modules take time to learn, components do not always integrate smoothly and optimization can be difficult.Read 15 Oct 2026 · trustradius.com
Limit: operational complexity
G2 reviewers complain that installation, NameNode administration, upgrades and security require substantial expertise and maintenance effort.Read 15 Oct 2026 · g2.com
Limit: small files and cloud fit
G2 reviewers report poor behavior with many small files and less flexibility or cost efficiency than cloud-native object storage.Read 15 Oct 2026 · g2.com
Maker profile
LinkedIn lists The Apache Software Foundation as a nonprofit software-development organization founded in 1999 with 5,001–10,000 employees and headquarters in Wilmington, Delaware.Read 15 Oct 2026 · linkedin.com
Namespace
HDFS offers hierarchical directories, permissions and quotas but does not support hard or soft links.Read 15 Oct 2026 · hadoop.apache.org
Operational tools
The user guide documents rack awareness, safemode, fsck, balancing, upgrade rollback and checkpointing utilities.Read 15 Oct 2026 · hadoop.apache.org
Praise: large-scale data
TrustRadius reviewers praise Hadoop for handling very large unstructured datasets, ETL pipelines, logging and broad data aggregation.Read 15 Oct 2026 · trustradius.com
Praise: reliability
G2 reviewers repeatedly praise HDFS for dependable large-file storage, fault tolerance and stable batch pipelines.Read 15 Oct 2026 · g2.com
Product purpose
HDFS is a distributed file system for high-throughput access to large datasets on commodity hardware.Read 15 Oct 2026 · hadoop.apache.org
Rating on G2
4.4 out of 5 from 141 reviewsRead 15 Oct 2026 · g2.com
Rating on TrustRadius
7.5 out of 10 from 270 reviews and ratingsRead 15 Oct 2026 · trustradius.com
Release verification
Apache distributes source and binary tarballs and recommends checking downloads for tampering with GPG signatures or SHA-512 checksums.Read 4 Oct 2026 · hadoop.apache.org
REST API depth
WebHDFS documents file, directory, quota, ACL, snapshot, storage-policy and erasure-coding operations.Read 15 Oct 2026 · hadoop.apache.org
Scale
HDFS is designed to scale to hundreds of nodes in a cluster and support tens of millions of files in one instance.Read 4 Oct 2026 · hadoop.apache.org
Security warning
Without Kerberos authentication, network users can have unrestricted access to data and execute code on the cluster.Read 15 Oct 2026 · hadoop.apache.org
Snapshots
HDFS snapshots preserve a point-in-time copy that can be used to roll back a corrupted instance.Read 15 Oct 2026 · hadoop.apache.org
System requirements
The documented production platform is GNU/Linux; Java is required and SSH/sshd is needed for remote daemon scripts.Read 15 Oct 2026 · hadoop.apache.org
Workload fit
HDFS is tuned for batch processing and streaming throughput rather than low-latency interactive use.Read 4 Oct 2026 · hadoop.apache.org
Write behavior
Files follow a write-once, read-many model, with appends and truncates supported but arbitrary in-place updates unavailable.Read 4 Oct 2026 · hadoop.apache.org

Plans and prices

Apache Hadoop HDFS Free Open-source software · Apache License 2.0 Read 4 Oct 2026 · hadoop.apache.org
Apache Hadoop / HDFS open-source distribution Free self-hosted · download from Apache mirrors · no hosted SLA stated Read 15 Oct 2026 · hadoop.apache.org

Every Apache Hadoop HDFS plan and price →

Strong points and limits

Strong points

  • Free, open-source software under Apache License 2.0.
  • Replicates file blocks across machines.
  • Supports clusters of hundreds of nodes.
  • Offers Java, C, REST, browser and NFS access.
  • Transparent encryption is supported.

Limits

  • Not designed for low-latency interactive workloads.
  • Arbitrary in-place file updates are unavailable.
  • Clusters need Kerberos authentication for caller access controls.
  • Production deployment requires securing the cluster.

Who it suits

HDFS suits teams that need distributed, high-throughput storage for batch or streaming workloads and can operate a self-hosted cluster. It is less suited to interactive work that depends on low-latency access or frequent in-place file updates.

Verdict

HDFS is built for scale and throughput, with a file model suited to batch and streaming work. Before production use, account for its update limits and secure the cluster with caller authentication.

Where Specifiction places it

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