# OpenObserve vs Chronosphere

> Open-source Chronosphere alternative: keep full-fidelity logs, metrics & traces on object storage instead of paying an enterprise platform to down-sample.

Source: https://openobserve.ai/chronosphere-alternative/
Competitor: Chronosphere

---

Cost control by architecture, not by dropping data. Open source and self-hostable. See why teams choose OpenObserve over Chronosphere.

- **140x** Lower storage costs compared to Elasticsearch
- **21,000+** Github Stars
- **9,000+** Companies trust us

Stop paying an enterprise platform to shrink your data; object storage makes full-fidelity retention affordable. [See transparent, ingest-based pricing →](/pricing/)

*Chronosphere does not publish pricing; contracts are typically custom enterprise agreements based on data throughput and persistence. Compare against OpenObserve's public usage-based pricing.*

- [Request Demo](/demo/)
- [Start Free](https://cloud.openobserve.ai/web/login)

## Why teams switch from Chronosphere

The many reasons that teams are making the switch

### Transparent Pricing, No Enterprise Contracts

Chronosphere pricing is custom and quote-only. OpenObserve has public, usage-based pricing and a free tier; start today, no sales cycle.

### Keep Full-Fidelity Data

Chronosphere's control plane cuts costs by aggregating and dropping telemetry. Object storage makes it cheap to keep everything instead.

### Self-Host, Cloud, or Air-Gapped

Chronosphere is SaaS-only. OpenObserve runs anywhere: single binary, HA cluster via Helm, or fully managed cloud.

### Logs, metrics, traces unified

One engine for all signals, not a metrics-first platform with separate purpose-built stores bolted on for logs and traces.

### Truly Open Source

Chronosphere builds on open standards but the platform is proprietary. OpenObserve's source is open; inspect it, run it, extend it.

### No Cardinality Bookkeeping

No per-series billing to profile, shape, and re-negotiate. Stateless compute over object storage keeps costs predictable as cardinality grows.

## See how OpenObserve replaces Chronosphere

Get a personalized walkthrough and see how much you'd save with cost control built into the architecture instead of an enterprise contract.

- 30-minute personalized walkthrough
- No credit card required
- See your real migration path from Chronosphere

## Feature comparison

Modern, full-stack observability

| Feature | Chronosphere | OpenObserve | Reference Links |
| --- | --- | --- | --- |
| Feature parity: logs, metrics, traces, dashboards, alerts, pipelines | ✓ | ✓ | [Logs](/docs/user-guide/data-exploration/logs/#overview), [Metrics](/docs/user-guide/data-exploration/metrics/), [Traces](/opentelemetry/), [Dashboards](/docs/user-guide/analytics/dashboards/dashboards-in-openobserve/), [Alerts](/docs/user-guide/analytics/alerts/), [Pipelines](/docs/user-guide/data-processing/pipelines/pipelines/) |
| Open Source | ✗ Proprietary SaaS (built on open standards) | ✓ | [View on GitHub](https://github.com/openobserve/openobserve) |
| Deployment options | SaaS only | Self-hosted, cloud, or air-gapped | [Learn more about Deployment options](/docs/architecture/) |
| Pricing transparency | Custom enterprise contracts, no public pricing | Public usage-based pricing with a free tier | [See pricing](/pricing/) |
| Cost-control approach | Control plane: aggregate, down-sample, and drop data to manage spend | Cheap by architecture: object storage + stateless compute, keep full-fidelity data | [Learn more about Cost-control approach](/docs/administration/maintenance/storage-management/) |
| Query language | PromQL (metrics-first), separate query experiences per signal | SQL + PromQL across signals | Used universally with no learning curve |
| Data storage | Vendor-managed, priced on data throughput and persistence | Your own S3/GCS/Azure bucket in open Apache Parquet format | [Learn more about Data storage](/docs/administration/maintenance/storage-management/) |
| OpenTelemetry support | ✓ | ✓ OTel-native (OTLP for logs, metrics, traces) | [OpenTelemetry](/opentelemetry/) |
| High-cardinality metrics | Strong at scale, but cardinality drives cost and requires shaping rules | No per-series pricing; cardinality doesn't require rule maintenance | [Learn more about High-cardinality metrics](/docs/user-guide/data-exploration/metrics/) |
| Getting started | Enterprise sales cycle and onboarding | Single binary or free cloud account: POC in minutes | [Quickstart](/docs/quickstart/) |
| IAM & SSO | ✓ | ✓ | [SAML, OIDC, LDAP, role-based access](/docs/user-guide/account-administration/identity-and-access-management/) |

## Migrating from Chronosphere

Because both platforms speak open standards, migration is mostly a collector reconfiguration, not a re-instrumentation project.

### Add OpenObserve as a second destination

You're already shipping via the OpenTelemetry Collector, Prometheus remote write, or Fluent Bit. Add an OTLP or remote-write exporter pointing at OpenObserve and dual-ship: no code or instrumentation changes.

### Recreate dashboards and alerts

Your PromQL queries and recording-rule logic carry over. Rebuild key dashboards in OpenObserve, add SQL for logs and traces, and configure alerts with equal or better granularity.

### Validate, cut over, and simplify

Run both platforms in parallel, compare results under real production load, then shift traffic. Retire aggregation and drop rules you only maintained to control the bill. Our team can help accelerate this process.

> OpenObserve is super fast, definitely very lightweight, and you can get started with an initial POC in two to three minutes to be honest.
> - Ajith Natarajan, Lead Software Engineer, Radius.ai

- [Talk to Our Migration Team](#demo-form)
- [Read Migration Stories](/customer-stories/)

## Frequently Asked Questions

Common questions about switching from Chronosphere to OpenObserve

### Is OpenObserve a good Chronosphere alternative?

Yes, for most teams. Both are OpenTelemetry-friendly platforms covering logs, metrics, and traces. The difference is the model: Chronosphere is a proprietary, SaaS-only enterprise platform whose cost story centers on a control plane that aggregates and drops data. OpenObserve is open source, self-hostable or cloud, and keeps costs low by architecture, stateless compute over object storage, so you can afford to keep full-fidelity data. If you want an open, portable stack without an enterprise contract, OpenObserve is a strong fit.

### How does OpenObserve pricing compare to Chronosphere?

Chronosphere doesn't publish pricing; contracts are custom enterprise agreements typically based on data throughput and persisted data, and reviewers note the billing model (including cardinality) takes real effort to understand and manage. OpenObserve publishes usage-based pricing, offers a generous free tier, and the open-source version is free to self-host with storage on your own object storage bucket at commodity prices.

### How much effort is migrating from Chronosphere?

Usually less than migrating from a proprietary-agent platform. If you ingest via the OpenTelemetry Collector, Prometheus remote write, or Fluent Bit, migration is a collector/exporter reconfiguration: dual-ship to both platforms, rebuild key dashboards and alerts (PromQL carries over), validate for a few weeks, then cut over. Teams replacing the Chronosphere Collector swap in the vendor-neutral OpenTelemetry Collector. Plan 4-8 weeks for typical setups; longer if you have extensive aggregation rules and derived metrics to review.

### Will I lose anything by leaving Chronosphere?

Be honest about your use case. Chronosphere is genuinely strong at massive-scale Prometheus metrics (its M3 heritage), its control plane tooling for profiling and shaping metric volume is best-in-class, and its support is highly rated. If you operate at extreme metrics scale and want a fully managed vendor to own that problem, Chronosphere earns its price. OpenObserve covers core observability, logs, metrics, traces, dashboards, alerts, pipelines, and removes the need for much of the shaping workflow, because retaining data on object storage is cheap in the first place.

### Do I still need aggregation and drop rules with OpenObserve?

Mostly no. With Chronosphere, shaping rules are how you keep the bill down: useful, but a workflow you must staff and maintain. With OpenObserve, data lands in compressed Parquet on object storage, so retention is cheap enough that most teams simply keep raw data. OpenObserve pipelines are still available when you want to redact, enrich, or route data, but as a choice, not a billing requirement.

### Can I self-host OpenObserve? Is it really open source?

Yes. Chronosphere is SaaS-only; OpenObserve's source code is open on GitHub and you can run it as a single binary on a laptop or as an HA cluster on Kubernetes via Helm, including fully air-gapped environments. You can also use OpenObserve Cloud if you'd rather not operate it. Either way your data lives in open Apache Parquet on your bucket, so there's no lock-in.

### Is OpenObserve enterprise-ready?

Yes. OpenObserve is SOC2 Type II certified and ISO 27001 compliant. We serve thousands of deployments, including Fortune 100 enterprises; our largest single customer ingests more than 4 PB of data per day, with individual clusters sustaining over 1 PB/day. Enterprise features include RBAC, SSO, sensitive data redaction, and dedicated support.

## Ready to See the Difference?

Get a personalized demo based on your current Chronosphere usage

## OpenObserve: the open-source Chronosphere alternative

An open-source, SQL and OpenTelemetry-native observability platform that gets cost control from architecture, object storage and stateless compute, instead of down-sampling. Radius.ai got started with a working POC in minutes, not months. Also evaluating other tools? See how OpenObserve compares to [Datadog](/datadog-alternative/), [Grafana](/grafana-alternative/), [New Relic](/newrelic-alternative/).

- Full-fidelity data on object storage: no drop rules required
- Open source, self-hosted or cloud: no SaaS-only lock-in
- Public usage-based pricing: no enterprise contract to start