Apache Hadoop HDFS vs HPCC Systems
Apache Hadoop HDFS
hadoop.apache.org
HPCC Systems
hpccsystems.comSide by side
| Figure | Apache Hadoop HDFS | HPCC Systems |
|---|---|---|
| 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 | 3 |
| Spec score · Data Lake Software | 8.9 (#1) | 8.7 (#2) |
| Architecture | A cluster uses a NameNode for namespace and access coordination and DataNodes for block storage and serving reads and writes. | The platform includes the ECL programming language, Thor data-refinery engine, and Roxie data-delivery engine. |
| 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. | The download page identifies version 10.6 as the latest platform release. |
| Encryption | HDFS documentation includes transparent encryption as a supported feature. | ECL can encrypt output data with 256-bit AES and compress it with LZW before serialization. |
| 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. | Official integrations include Spark, Kafka, Couchbase, Redis, Memcached, Pentaho, R, JDBC, Java APIs and Tableau data connectors. |
| License | Apache packages are generally distributed under the OSI-approved Apache License 2.0 unless a package states otherwise. | The Community Edition is licensed under the Apache License 2.0. |
| Limit: operational complexity | G2 reviewers complain that installation, NameNode administration, upgrades and security require substantial expertise and maintenance effort. | Business-Software.com characterizes the delivery system as complex even though it is designed for rigorous service levels and low latency. |
| Purpose | HDFS is a distributed file system designed for high-throughput access to large application data sets on commodity hardware. | HPCC Systems is an open-source, data-intensive supercomputing platform for enterprise big-data problems. |
| Scale | HDFS is designed to scale to hundreds of nodes in a cluster and support tens of millions of files in one instance. | Clusters can scale from two computers to more than a thousand commodity-hardware nodes. |
| Security | Production clusters are expected to use Kerberos for caller authentication and access control. | Cloud-native security features include end-to-end encryption, Linkerd or Istio service meshes, OAuth 2.0 with Azure AD support, and JWT. |
| System requirements | The documented production platform is GNU/Linux; Java is required and SSH/sshd is needed for remote daemon scripts. | A single-node installation requires a current supported Linux system; the FAQ states a 4 GB minimum per node and commodity hardware support. |
Plans
Apache Hadoop HDFS
- Apache Hadoop HDFSFree
- Apache Hadoop / HDFS open-source distributionFree
HPCC Systems
- Community EditionFree
- Open sourceFree
- Enterprise subscriptionPriced on request
In their own words
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.
HPCC Systems
HPCC Systems is a free, open-source platform for enterprise big-data processing and data-lake management. Its core components are ECL, a declarative and modular language, Thor for data refinement, and Roxie for data delivery. ECL's compiler optimizes programs for parallel processing and compiles them into C++. Thor handles ingestion, transformation, linking, and indexing; Roxie serves concurrent queries. Clusters can scale from two computers to more than a thousand commodity-hardware nodes. The cloud-native platform runs on Kubernetes and supports Azure Kubernetes Service and Amazon Elastic Kubernetes Service. Storage options include AWS S3, Azure Blob Storage, AWS Elastic Block Store, Azure Files, and Azure Disks. Security capabilities include end-to-end encryption, service meshes, OAuth 2.0 with Azure AD support, JWT, and configurable controls for data and services. The Machine Learning Library offers ECL-accessible algorithms for building and testing prediction models. Integrations include Spark, Kafka, Couchbase, Redis, Memcached, Pentaho, R, JDBC, Java APIs, and Tableau data connectors. ESP exposes queries through XML, HTTP, SOAP, and REST interfaces, and deployed queries can be called with REST/JSON. The platform is free to use under the Apache 2.0 license and is self-hosted.