About Vector
Vector is a high-performance observability data pipeline that works both as an agent and as an aggregator. It collects logs and metrics from many sources, transforms them, and routes them to whichever vendors or storage systems you choose, so you can switch or combine backends without changing how data is collected.
The project argues that this gives you control over your telemetry: you can cut costs by filtering and shaping data before it reaches a paid vendor, enrich events in new ways and apply data security where you need it rather than where it is most convenient for a vendor. It also claims to be substantially faster than comparable tools. Built in Rust, its primary design goal is reliability, and topics mention traces, stream processing and ETL.
Datadog's open-source engineering team maintains Vector, which is licensed under MPL-2.0. The README offers a quickstart, installation guides, integrations and container images. Because it is software you run yourself, it needs no hosted service, and it suits platform and SRE teams that manage large volumes of logs and metrics.
Key features
- Collects logs and metrics from many sources
- Transforms and enriches events in flight
- Routes data to multiple destinations
- Runs as agent or aggregator
- Written in Rust for reliability
- Container images and install guides
Good fit for
- →Reducing observability costs by filtering data
- →Switching log vendors without reconfiguring apps
- →Central log and metric routing
- Built with
- Rust
- Tags
- observability
- logs
- metrics
- data-pipeline
- rust
- telemetry
- etl
- monitoring
- datadog
Vector: questions and answers
- What is Vector used for?
- Vector is a Rust-based observability data pipeline from Datadog's open-source team that collects, transforms and routes logs and metrics to any destination. It is a good fit for reducing observability costs by filtering data, switching log vendors without reconfiguring apps, and central log and metric routing.
- Is Vector open source?
- Yes. Vector is open source under the MPL-2.0 licence. Its source code is on GitHub at vectordotdev/vector and is written mainly in Rust.
- Is Vector free?
- Yes. Vector is open source, so the software itself is free to use.
- Can I self-host Vector?
- Yes. Vector can be self-hosted on your own server or infrastructure; there is no official hosted version.
- What is Vector an alternative to?
- Vector is an open-source alternative to Cribl and Mezmo. Other open-source alternatives to Cribl include OpenTelemetry Collector, Telegraf and Grafana Alloy.
- Is Vector actively maintained?
- Yes. The most recent commit to Vector was on 2 October 2026. The project has 23k stars on GitHub.
Open-source alternatives to Vector
See all
OpenTelemetry Collector
Monitoring & Observability
OpenTelemetry Collector
Apache-2.0vs Cribl★ 7.6k
Telegraf
Monitoring & Observability
Agent for collecting, processing, aggregating, and writing metrics, logs, and other arbitr
MITvs Cribl★ 18k
Grafana Alloy
Monitoring & Observability
OpenTelemetry Collector distribution with programmable pipelines
Apache-2.0vs Cribl★ 3.6k
Logstash
Data Pipelines & ETL
Logstash - transport and process your logs, events, or other data
OSSvs Cribl★ 15k
OpenObserve
Monitoring & Observability
High-performance, unified observability for the AI era. 140x lower storage cost.
AGPL-3.0vs Datadog★ 22k
Grafana Loki
Monitoring & Observability
Like Prometheus, but for logs.
AGPL-3.0vs Datadog★ 29k
SaaS alternatives to Vector
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Cribl
Monitoring & Observability
Telemetry pipeline that routes, reduces and enriches logs and metrics
SaaS
Mezmo
Monitoring & Observability
Telemetry pipeline and log analysis platform
SaaS
Amazon CloudWatch
Monitoring & Observability
AWS service for metrics, logs, alarms and dashboards
SaaS
Azure Monitor
Monitoring & Observability
Azure service for collecting and analyzing metrics, logs and traces
SaaS
Coralogix
Monitoring & Observability
Observability platform that analyzes logs, metrics and traces as they are ingested
SaaS
New Relic
Monitoring & Observability
Observability platform for application performance, infrastructure and logs
SaaS
