# Big Data

Talend Studio supports big data processing with Hadoop technologies such as HDFS, Hive, and HBase.

Big data describes datasets that are too large or complex for traditional processing approaches. These datasets often come from logs, events, and transactions.

Hadoop-based environments process data in parallel across multiple nodes. This model helps scale storage and computation for large workloads.

Talend Studio lets you design Jobs that read, transform, and write data in Hadoop ecosystems without writing all framework code manually.

Information noteTip: Hadoop supports multiple file compression formats. Compression can reduce storage usage and improve data transfer performance. In a Job, process compressed files directly using file system components such as tHDFSConfiguration and tFileInputDelimited.

### In this section

* [Designing Spark Jobs](https://help.qlik.com/talend/en-US/studio-user-guide/8.0-R2026-09/designing-spark-jobs)
* [Advanced Big Data Job Operations](https://help.qlik.com/talend/en-US/studio-user-guide/8.0-R2026-09/handling-big-data-jobs)
* [Dynamic support for Hadoop distributions in Talend Studio (deprecated)](https://help.qlik.com/talend/en-US/studio-user-guide/8.0-R2026-09/dynamic-support-for-hadoop-distributions-in-talend-studio)
* [Spark Universal support for Hadoop distributions in Talend Studio](https://help.qlik.com/talend/en-US/studio-user-guide/8.0-R2026-09/spark-universal-support-for-hadoop-distributions-in-talend-studio)