Cribl vs Vector -- Security Data Pipeline Compared

Cribl vs Vector

Vector offers the highest raw performance of any open-source observability pipeline thanks to its Rust implementation, with strong data transformation via VRL. Cribl provides a more complete commercial platform with a GUI pipeline designer, broader enterprise integrations, advanced data reduction, and dedicated enterprise support.

The Verdict

Choose Vector if you need the highest-performance open-source pipeline with Rust-based reliability and are comfortable with CLI-based configuration. Choose Cribl if you need a complete commercial platform with a GUI designer, enterprise integrations, advanced data reduction, and dedicated support.

Feature-by-Feature Comparison

FeatureVectorCribl
PerformanceRust-based, highest throughputHigh throughput, custom engine
Open SourceYes (MPL 2.0)Free tier, commercial product
Transform LanguageVRL (Vector Remap Language)Custom pipeline expressions
User InterfaceCLI and config filesFull GUI pipeline designer
Data ReductionTransform-based filteringAdvanced reduction (40-70%)
Enterprise SupportCommunity (Datadog-backed)Full enterprise support
Delivery GuaranteesEnd-to-end acknowledgementsAt-least-once delivery
Data ReplayNot built-inFull replay and rehydration

When to Choose Each Tool

Choose Vector when:

  • +You need the highest possible pipeline throughput and performance
  • +You want an open-source solution with no licensing costs
  • +You prefer a modern Rust-based tool with low resource usage
  • +You need end-to-end delivery acknowledgements
  • +Your team is comfortable with CLI-based pipeline configuration

Choose Cribl when:

  • +You need a GUI-based pipeline designer for complex workflows
  • +You want the broadest enterprise integration ecosystem
  • +You need advanced data reduction and cost optimization
  • +You require enterprise support and SLAs
  • +You need data replay and rehydration capabilities

Pros & Cons Comparison

Vector

Pros

  • +Exceptional performance from Rust implementation
  • +Low resource footprint for high throughput
  • +Powerful VRL transform language
  • +End-to-end delivery guarantees
  • +Active open-source community (Datadog-backed)

Cons

  • VRL has a learning curve
  • Smaller plugin ecosystem than Fluentd
  • Datadog ownership raises vendor neutrality concerns
  • No built-in GUI for pipeline design
  • Less mature ecosystem compared to Cribl

Cribl

Pros

  • +Dramatically reduces SIEM ingest costs
  • +Vendor-agnostic routing to any destination
  • +Powerful data transformation and enrichment
  • +Free tier for small deployments
  • +Active community and extensive documentation

Cons

  • Adds another layer to manage in the data pipeline
  • Enterprise pricing can be expensive at scale
  • Steep learning curve for advanced pipeline logic
  • Self-hosted deployment requires infrastructure expertise
  • Limited built-in analytics — requires downstream tools

Cribl vs Vector FAQ

Common questions about choosing between Cribl and Vector.

What is the main difference between Cribl and Vector?

Vector offers the highest raw performance of any open-source observability pipeline thanks to its Rust implementation, with strong data transformation via VRL. Cribl provides a more complete commercial platform with a GUI pipeline designer, broader enterprise integrations, advanced data reduction, and dedicated enterprise support.

Is Vector better than Cribl?

Choose Vector if you need the highest-performance open-source pipeline with Rust-based reliability and are comfortable with CLI-based configuration. Choose Cribl if you need a complete commercial platform with a GUI designer, enterprise integrations, advanced data reduction, and dedicated support.

How much does Vector cost compared to Cribl?

Vector pricing: Free (open source, MPL 2.0). Cribl pricing: Free (up to 1 TB/day) / Enterprise custom pricing. Vector's pricing model is open source, while Cribl uses volume-based (daily throughput) pricing.

Can I migrate from Cribl to Vector?

Yes, you can migrate from Cribl to Vector. The migration process depends on your specific setup and the features you use. Both platforms offer APIs that can facilitate automated migration. Consider running both tools in parallel during the transition to ensure zero downtime.

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