Apache Hadoop HDFS
7.1#3 in data lake softwareFree planFree planAPILinuxSelf-hostedWindows
VisitApache Hadoop HDFS vs Qubole
What both publish
| Fact | Apache Hadoop HDFS | Qubole |
|---|---|---|
| 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. | Qubole's Spark page lists authenticated ODBC/JDBC connections for Tableau and Looker, REST API integrations including Airflow and Oozie, and data connectors including Snowflake, Redshift, Kafka, and Kinesis. |
| Purpose | HDFS is a distributed file system designed for high-throughput access to large application data sets on commodity hardware. | Qubole describes its platform as an open, secure, multi-cloud data lake platform for machine learning, streaming analytics, data exploration, and ad-hoc analytics. |
| Support | The project asks users not to request private support from its non-paid volunteers and directs help requests to module mailing lists. | The pricing page says support is included with both Enterprise Edition and On-Demand plans. |
Apache Hadoop HDFS plans
- Apache Hadoop HDFSFree
- Apache Hadoop / HDFS open-source distributionFree
Qubole plans
- Free TrialFree
- Enterprise EditionPriced on request
- On-DemandPriced 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 Qubole if…
Qubole suits teams running data and analytics workloads across cloud providers, particularly those needing machine learning, streaming pipelines, or query and reporting tools. Its paid plans may also suit organizations seeking workload-aware resource management and stated security controls.