Axiom

About Axiom

Axiom is a machine data platform for ingesting, storing, and querying logs, traces, metrics, and events at scale. It provides a fully managed, schema-less event store with petabyte-scale ingest and over 95% compression, using a stream-oriented, schema-on-read architecture that avoids upfront index or schema decisions. Data can be explored through a query interface (APL, a piped query language) and a metrics-focused language (MPL), alongside dashboards, monitors, and stream views over datasets such as application logs, Kubernetes events, OpenTelemetry traces, and webhook data.

The platform is aimed at engineering teams running observability for backend services, infrastructure, and distributed systems who need to retain large volumes of telemetry without operating a self-managed cluster. It supports common data sources including OpenTelemetry, Vector, Fluent Bit, AWS Kinesis Firehose, Lambda, and GitHub and Vercel event data, and includes shared datasets for OpenTelemetry demo traces and Vercel web analytics.

Pricing is usage-based, billed per unit of ingest across logs, traces, metrics, and events, with volume discounts that apply automatically as usage increases. Axiom offers a permanent free tier as well as self-serve enterprise add-ons.

Key features

• Petabyte-scale, schema-less ingest on a fully managed event store with 95%+ compression
• Stream-oriented, schema-on-read architecture with virtual fields for query-time transformation
• No indexes to manage and no ingest-time schema decisions required
• Usage-based pricing with automatic volume discounts and a permanent free tier
• APL query language (piped, sequential, log-friendly) for logs, and MPL for metrics

Frequently asked questions