Multi-Destination Data Routing -- Cribl Alternatives
Multi-destination data routing is the ability to send the same data to multiple downstream systems simultaneously — SIEM for detection, data lake for retention, monitoring tools for operations, and archive for compliance. This fan-out capability is essential for organizations that need the same security data in multiple tools without paying ingest costs multiple times. These Cribl alternatives support multi-destination routing with different levels of flexibility and control.
Create a matrix of data sources and their required destinations. Each source may need to reach 2-5 destinations: SIEM for detection, data lake for retention, monitoring for operations, archive for compliance, and analytics for business intelligence.
Set up pipeline routes that duplicate and fan out data to multiple destinations simultaneously. Configure per-destination data transformation to shape data to each destination's expected format and schema.
Apply different optimization rules per destination. Send full-fidelity data to the data lake, reduced/enriched data to the SIEM, aggregated metrics to monitoring tools, and compliance-required fields to archive. Each destination receives exactly the data it needs.
Configure buffering, retry logic, and delivery acknowledgements for each destination. Set up dead-letter queues for data that cannot be delivered. Ensure that a failure at one destination does not block delivery to other destinations.
Deploy monitoring for delivery success rates, latency, and error rates per destination. Alert on destination failures, backpressure, and delivery lag. Track data volume per destination to verify routing logic and identify cost optimization opportunities.
Free (open source, MPL 2.0)
Native multi-destination routing with component-based architecture that allows complex fan-out topologies. VRL transforms enable per-destination data shaping, and end-to-end acknowledgements ensure delivery to all destinations.
Free (open source) / Commercial support via vendors
The copy output plugin enables simultaneous routing to multiple destinations from the same source. With 800+ plugins covering nearly every destination, Fluentd supports the broadest range of multi-destination routing scenarios.
From $0.10/GB processed / Enterprise custom
Managed multi-destination routing with pipeline monitoring that tracks delivery health to each destination. Sensitive data detection ensures PII is handled appropriately regardless of which destination receives the data.
From $0.80/GB ingested / Enterprise custom
Built-in multi-destination routing with the added benefit of using Mezmo itself as one of the destinations for log search and analytics. Simplifies architectures where log management is one of the target destinations.
Included with Splunk Cloud / Enterprise add-on pricing
Supports multi-destination routing within the Splunk ecosystem, directing data to different Splunk indexes, Splunk-connected S3 storage, and select third-party destinations. Best for Splunk-centric multi-destination needs.
High-performance open-source observability pipeline built in Rust by Datadog
Free (open source, MPL 2.0)
Teams wanting the highest-performance open-source pipeline with Rust-based reliability for high-throughput data routing
Open-source unified data collector and log aggregator from the CNCF ecosystem
Free (open source) / Commercial support via vendors
Cloud-native teams wanting a lightweight, proven open-source data collector with a massive plugin ecosystem
Managed observability pipeline for routing and transforming telemetry data at scale
From $0.10/GB processed / Enterprise custom
Organizations already using Datadog that want managed pipeline capabilities with enterprise support and monitoring
Log management and observability pipeline platform with intelligent data routing
From $0.80/GB ingested / Enterprise custom
Teams wanting combined log management and pipeline capabilities with a developer-friendly experience
Splunk's real-time stream processing engine for data optimization and routing
Included with Splunk Cloud / Enterprise add-on pricing
Existing Splunk customers wanting to optimize data flows and reduce ingest costs within the Splunk ecosystem
Modern security architectures require the same data in multiple tools: SIEM for real-time detection, data lake for long-term retention, monitoring for operational visibility, and archive for compliance. Without a pipeline, you either send all data to every tool (expensive) or choose one destination per source (losing visibility). Multi-destination routing lets you send the right data to each tool, optimized for its specific purpose, from a single collection point.
With a data pipeline, you collect data once and route copies to each destination. You pay ingest costs at each destination, but the pipeline allows you to optimize data differently per destination — full data to the data lake (cheap storage), reduced data to the SIEM (expensive ingest), and aggregated data to monitoring (moderate cost). This is significantly cheaper than collecting and sending full data independently to each tool.
Production pipelines should be configured so that one destination's failure does not block delivery to others. Vector and Fluentd support independent output buffers per destination with separate retry logic. Configure disk-based buffering to handle temporary outages and dead-letter queues for persistent failures. Monitor each destination independently and set up alerting for delivery failures.
Yes. Modern data pipelines support per-destination data transformation. You can send JSON to your SIEM, Parquet to your data lake, and metrics to your monitoring platform — all from the same source data. The pipeline transforms and formats data for each destination's expected schema. This is one of the key advantages of a centralized pipeline over point-to-point integrations.
High-performance open-source observability pipeline built in Rust by Datadog
ComparisonOpen-source unified data collector and log aggregator from the CNCF ecosystem
ComparisonManaged observability pipeline for routing and transforming telemetry data at scale
CategoryCompare the best open source data pipeline alternatives to Cribl in 2026. Fluentd, Vector, Tenzir — features, performance, and deployment compared.
CategoryCompare the best cloud data pipeline alternatives to Cribl in 2026. Datadog Observability Pipelines, Mezmo, Observo AI — features, pricing, and capabilities compared.
Use CaseCompare the best Cribl alternatives for log routing and optimization in 2026. Fluentd, Vector, Mezmo, Datadog Pipelines — routing capabilities, pricing, and features compared.
Use CaseCompare the best Cribl alternatives for SIEM data optimization in 2026. Observo AI, Splunk DSP, Datadog Pipelines, Mezmo — SIEM cost reduction capabilities compared.
Use CaseCompare the best Cribl alternatives for building a security data lake in 2026. Azure Data Explorer, Vector, Tenzir, Fluentd — data lake routing and architecture compared.