How VectorFlow compares
Where VectorFlow fits relative to Cribl Stream, Datadog Observability Pipelines, Edge Delta, Mezmo, Splunk Edge Processor, Grafana Alloy, and other observability pipeline tools.
VectorFlow is a self-hosted control plane for Vector data pipelines. It is not an observability backend, a SaaS log search product, or a vendor-lock-in alternative — and it does not try to be. This page is here so you can decide quickly whether VectorFlow is the right tool for what you are doing.
What VectorFlow is
- A web UI to design Vector pipelines visually instead of hand-editing TOML.
- A fleet manager that pushes pipeline configs to
vf-agentprocesses running alongside Vector on your hosts. - A monitoring layer for the pipelines themselves: throughput, error rates, host metrics, anomalies, cost.
- AGPL-3.0 open source, runs on your own infrastructure, your data never leaves your network.
What VectorFlow is not
- Not a log search / metrics / tracing backend. Vector still ships the data to your existing destinations (Datadog, Splunk, S3, Elasticsearch, Loki, Kafka, ClickHouse, etc.).
- Not a SaaS. There is no managed VectorFlow cloud; you run the server yourself.
- Not a Vector replacement. VectorFlow generates Vector configuration; the data plane is still Vector.
Where VectorFlow fits
| You are... | VectorFlow is... |
|---|---|
| Already running Vector and tired of managing TOML across hosts | The natural next step. Visual editor, fleet rollout, version history, rollback. |
| Evaluating an observability pipeline tool because you want to cut backend costs (filter, sample, route) | A self-hosted option that keeps you on Vector. No per-GB pricing, no proprietary engine. |
| Looking for a SaaS pipeline product with managed infrastructure and a sales motion | Not the right tool. Look at Cribl Cloud, Datadog Observability Pipelines, Edge Delta, or Mezmo. |
| Looking for a log search / SIEM product | Not the right tool. VectorFlow shapes data; it doesn't store or query it. |
Side-by-side
The table below is intentionally narrow: it covers tools people already evaluate against VectorFlow. It is not exhaustive.
| VectorFlow | Cribl Stream | Datadog Observability Pipelines | Edge Delta | Splunk Edge Processor | Grafana Alloy / Fleet | |
|---|---|---|---|---|---|---|
| Data engine | Vector (vector.dev) | Cribl LogStream (proprietary) | Worker proxy fronting Datadog Agent | Edge Delta agent (proprietary) | Splunk SPL pipelines (proprietary) | Grafana Alloy (OTel collector fork) |
| Self-hosted, no SaaS dependency | Yes | Yes (Stream) — but commercial license | No (control plane is SaaS) | No (control plane is SaaS) | Tied to Splunk Cloud / Enterprise | Yes |
| Open source license | AGPL-3.0 | Proprietary (free tier ≤1 TB/day) | Proprietary | Proprietary | Proprietary | Apache-2.0 (Alloy) |
| Visual pipeline editor | Yes | Yes | Yes | Yes | Limited | No (config-as-code) |
| Vendor lock-in for the data plane | None — Vector is open source | High — Cribl-only routes/functions | Datadog Agent / Datadog backend | Edge Delta agent | Splunk | None — Alloy is OTel-compatible |
| Pricing model | Free | Per ingested GB/day | Per host + per GB | Per GB | Splunk licensing | Free |
| Where data is stored | You decide (Vector sinks) | You decide (Cribl outputs) | Datadog (default) | Edge Delta or your sinks | Splunk (default) | You decide (Alloy outputs) |
| Fleet rollout / version history / rollback | Yes | Yes | Yes | Yes | Yes | Via Grafana Fleet (paid) |
| Anomaly detection on pipelines | Yes | Yes | Yes | Yes | No | No |
| Runs on your laptop / homelab | Yes (Docker Compose) | Free tier yes | No | No | No | Yes |
Sources: vendor websites and public docs as of 2026. Pricing and tiers change frequently — check the vendor before committing.
Honest comparison points
Cribl Stream
Cribl is the closest commercial analog to VectorFlow in shape — visual pipeline editor, fleet, routing, sampling, redaction. Differences:
- Cribl runs on a proprietary engine. Your routes and functions only work in Cribl.
- Cribl has a deeper feature set today: more first-party integrations, more processing functions, more polished enterprise features.
- Cribl has a free tier (≤1 TB/day) but is a commercial product above that. VectorFlow is AGPL-3.0 with no usage cap.
- VectorFlow keeps you on Vector, which is also used by Datadog (acquired Timber.io), so your pipelines are portable to other Vector deployments.
Pick Cribl if you need a turnkey commercial product with vendor support and you're OK with proprietary lock-in. Pick VectorFlow if you want a Vector-native control plane and AGPL is fine.
Datadog Observability Pipelines
Datadog OP is fundamentally a control plane in front of the Datadog Agent / Vector worker. It is positioned as a way to feed Datadog more efficiently, not as a destination-agnostic tool.
- Control plane is SaaS-only, hosted by Datadog.
- Pricing is on top of existing Datadog infrastructure.
- Best leverage if Datadog is already your observability backend.
Pick Datadog OP if you're already on Datadog and want pipeline control plane with the same vendor. Pick VectorFlow if you want self-hosted and destination-agnostic.
Edge Delta
Edge Delta does heavy edge analytics — pre-aggregating, anomaly detection, partial materialization at the agent — to reduce backend cost. It is more than a pipeline; it does some processing that would otherwise happen in your backend.
- SaaS-managed control plane.
- Proprietary agent.
- Strong on edge intelligence; less strong as a generic Vector-style router.
Pick Edge Delta if edge analytics + per-GB cost reduction matters more than data-plane portability. Pick VectorFlow if you want a transparent Vector pipeline you can audit and self-host.
Mezmo (formerly LogDNA Pipeline)
Mezmo Pipeline is a SaaS pipeline product with a visual editor.
- SaaS only. Your data flows through Mezmo's control plane.
- Pricing per GB ingested through pipelines.
Pick Mezmo if you want a low-effort SaaS pipeline tool. Pick VectorFlow if you can't or won't route data through a third-party SaaS.
Splunk Edge Processor
Edge Processor pre-processes data before it reaches Splunk Cloud. Not really a destination-agnostic pipeline tool.
- Tightly coupled to Splunk Cloud.
- Limited routing to non-Splunk destinations.
Pick Edge Processor if you're a Splunk shop. Pick VectorFlow if you have multiple destinations or aren't on Splunk.
Grafana Alloy / Fleet
Alloy is Grafana's OpenTelemetry-compatible collector (a fork of the OTel Collector / Grafana Agent line). It overlaps with Vector as a data plane, not directly with VectorFlow.
- No native visual pipeline editor — config-as-code (River).
- Fleet management is via Grafana Fleet (paid Grafana Cloud feature) or roll-your-own (Ansible, Salt, etc.).
- OTel-native; Vector is broader (logs, metrics, traces with VRL transformation).
Pick Alloy if you're committed to OpenTelemetry and prefer config-as-code. Pick VectorFlow if you want Vector's flexibility plus a UI and built-in fleet management.
Calyptia / Chronosphere
Calyptia (acquired by Chronosphere) builds tools around Fluent Bit — a different data plane from Vector. Different ecosystem, different operational model.
Pick Calyptia if Fluent Bit is your standard. Pick VectorFlow if Vector is.
When VectorFlow is genuinely the wrong choice
We'd rather you pick the right tool than try to use VectorFlow against the grain.
- You need a fully managed SaaS with vendor SLAs and 24/7 support. VectorFlow is self-hosted open source. There is no managed offering yet.
- You need a search / analysis backend. VectorFlow shapes and routes data; it doesn't store or query it. Pair it with Loki, Elasticsearch, ClickHouse, Splunk, Datadog, etc.
- You're committed to OpenTelemetry as the agent. Use Alloy or the OTel Collector. Vector supports OTLP receivers/exporters but is not itself an OTel collector.
- You have fewer than 50 nodes and don't change pipelines often. Hand-editing Vector TOML and pushing it with Ansible is genuinely fine at small scale.
Source code and license
VectorFlow is AGPL-3.0 on GitHub. The AGPL means: if you modify VectorFlow and run the modified version as a service that other parties interact with over a network, you must publish your changes. For internal use within your own organization, AGPL behaves like GPL — modify freely, no obligation to publish.
If you want a different license, open an issue — we may consider commercial licensing for specific embedded use cases.