Splunk Data Stream Processor

Splunk's real-time stream processing engine for data optimization and routing

Enterprise Data PipelineIncluded with Splunk Cloud / Enterprise add-on pricing
How we work:This listing is aggregated from Splunk Data Stream Processor's official documentation, public pricing pages, community discussions (Reddit, HN, forums), and real user feedback. We do not do hands-on testing. We aggregate and organize what's already out there. Last verified February 2026.

What is Splunk Data Stream Processor?

Splunk Data Stream Processor (DSP) is Splunk's real-time stream processing engine designed to collect, process, and deliver data at scale. Built on Apache Flink, DSP enables organizations to filter, mask, enrich, and route data in real time before it reaches Splunk or other destinations. It is positioned as a complement to Splunk Enterprise for organizations that need to optimize data flows and reduce ingest costs.

Best for: Existing Splunk customers wanting to optimize data flows and reduce ingest costs within the Splunk ecosystem
Pros
  • Tight integration with Splunk ecosystem
  • Familiar SPL-based pipeline language
  • Built on proven Apache Flink engine
  • Reduces Splunk ingest costs
  • Managed as part of Splunk Cloud
Cons
  • Tightly coupled to Splunk ecosystem
  • Less flexible than vendor-agnostic alternatives
  • Limited non-Splunk destination support
  • Additional cost on top of Splunk licensing
  • Less community adoption and fewer resources

Key Features

Real-time stream processing (Apache Flink)
Data filtering and masking
Enrichment with lookup tables
Multi-destination routing
SPL2 pipeline language
Pre-built data functions
Splunk HEC integration
Schema-on-read processing