Apache Hadoop HDFS
7.1#3 in data lake softwareFree planFree planAPILinuxSelf-hostedWindows
VisitApache Hadoop HDFS vs HPCC Systems
HPCC Systems
7.5#1 in data lake softwareFree planFree planWebAPIExtensionLinux
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| Fact | Apache Hadoop HDFS | HPCC Systems |
|---|---|---|
| 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. |
Apache Hadoop HDFS plans
- Apache Hadoop HDFSFree
- Apache Hadoop / HDFS open-source distributionFree
HPCC Systems plans
- Open sourceFree
- Community EditionFree
- Enterprise subscriptionPriced on request
Pick Apache Hadoop HDFS if…
HDFS suits teams handling large application data sets that need distributed storage for batch or streaming workloads. It is less suited to interactive work requiring low latency or arbitrary in-place file updates.
Pick HPCC Systems if…
HPCC Systems suits organizations building data lakes or processing large, mixed-schema datasets that can manage a self-hosted platform. It may also fit teams that need parallel processing, query interfaces, or ECL-accessible machine-learning algorithms.