Apache Beam vs Apache Hadoop HDFS
Apache Beam
beam.apache.org
Apache Hadoop HDFS
hadoop.apache.orgSide by side
| Figure | Apache Beam | Apache Hadoop HDFS |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | Yes | Yes |
| Web | Yes | — |
| Windows | Yes | Yes |
| macOS | Yes | — |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 2 | 2 |
| Spec score · Big Data Analytics Software | 9.1 (#1) | 8.8 (#6) |
| License | Apache Beam is distributed by the Apache Software Foundation under the Apache License version 2.0. | Apache packages are generally distributed under the OSI-approved Apache License 2.0 unless a package states otherwise. |
| Rating on G2 | 4.1 out of 5 from 16 reviews | 4.4 out of 5 from 141 reviews |
| Security | Apache release files include OpenPGP signatures and SHA-512 checksums so users can verify downloaded files. | Production clusters are expected to use Kerberos for caller authentication and access control. |
| Support | Beam users can get community support through the user mailing list, Stack Overflow, and the Beam Slack channel. | The project asks users not to request private support from its non-paid volunteers and directs help requests to module mailing lists. |
Plans
Apache Hadoop HDFS
- Apache Hadoop HDFSFree
- Apache Hadoop / HDFS open-source distributionFree
In their own words
Apache Beam
Apache Beam is an open-source programming model for building data-processing pipelines across batch and streaming workloads. The same model can support both patterns in production, while runners provide different execution back ends, including Dataflow, Flink, Spark, and the Direct Runner. SDKs and quickstarts cover Java, Python, Go, and TypeScript. Pipeline building blocks include ParDo, GroupByKey, Flatten, and Combine, alongside windowing and triggering. Beam I/O connectors supply read and write transforms for external storage in batch or streaming pipelines, with catalog examples such as BigQuery, Snowflake, Apache Parquet, and Apache Iceberg. Beam Playground provides a way to try examples and transforms without a local installation. The software is free and open source; the listed plan is free, but execution costs depend on the runner and infrastructure selected. It targets data and software developers building pipelines on supported back ends. APIs may change before the first stable 1.x release, and semantic-versioning practice has exceptions.
Apache Hadoop HDFS
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.