Apache Hadoop HDFS
7.1#3 in data lake softwareFree planFree planAPILinuxSelf-hostedWindows
VisitApache Hadoop HDFS vs Parseable
What both publish
| Fact | Apache Hadoop HDFS | Parseable |
|---|---|---|
| Architecture | A cluster uses a NameNode for namespace and access coordination and DataNodes for block storage and serving reads and writes. | The product is written in Rust and uses an object-store-native, open columnar format. |
| 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. | The site lists integrations including Prometheus, Grafana, Kafka, Redpanda, AWS, Azure, OpenTelemetry, Kubernetes, Fluent Bit, Fluentd, Vector, MinIO, OpenAI, and Anthropic. |
| Security | Production clusters are expected to use Kerberos for caller authentication and access control. | The site identifies Parseable as GDPR certified and SOC 2 Type II. |
| Support | The project asks users not to request private support from its non-paid volunteers and directs help requests to module mailing lists. | The Enterprise plan includes premium support with a dedicated SLA, and the site lists 24×7 product support via portal in its plan comparison. |
Apache Hadoop HDFS plans
- Apache Hadoop HDFSFree
- Apache Hadoop / HDFS open-source distributionFree
Parseable plans
- OSSFree
- Cloud$0.39 a month
- Enterprise$15,000 a year
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 Parseable if…
Parseable suits teams that want logs, metrics, and traces in one observability platform, with a choice of self-hosted or managed deployment. The Enterprise plan is described for serious teams seeking enterprise-grade observability.