OpenObserve vs Logz.io
The same open-standards promise — actually open source. Self-host or cloud, keep data for months on object storage, and stop paying retention-tier fees.
TRUSTED BY INNOVATIVE TEAMS

Why teams switch from Logz.io
The many reasons that teams are making the switch
No Retention-Tier Fees
Logz.io prices hot retention per GB per day — more days, higher rate. OpenObserve keeps everything on cheap object storage.
Costs That Don't Scale With Volume
Per-GB-per-day pricing gets expensive fast as log volume grows. Columnar Parquet storage keeps OpenObserve costs predictable at scale.
Actually Open Source
Logz.io is built on open source but is SaaS-only. OpenObserve is open source itself — self-host anywhere or use our cloud.
One Engine, Not Three Stacks
Logz.io stitches together OpenSearch, Prometheus, and Jaeger. OpenObserve is a single engine for logs, metrics, and traces.
SQL Instead of Lucene
No Kibana/OpenSearch query learning curve. Query logs with standard SQL and metrics with PromQL — languages your team already knows.
Your Data, Your Bucket
Keep telemetry in your own S3/GCS/Azure bucket in open Apache Parquet format. No SaaS-only lock-in — switch anytime.
See how OpenObserve replaces Logz.io
Get a personalized walkthrough and see how much you'd save moving off volume-and-retention pricing.
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Feature comparison
Modern, full-stack observability
| Feature | Logz.io | OpenObserve | Reference Links |
|---|---|---|---|
| Feature parity: logs, metrics, traces, dashboards, alerts, pipelines | ✓ | ✓ | LogsMetricsTracesDashboardsAlertsPipelines |
| Open Source | ✗ Built on open source, but the platform is proprietary SaaS | ✓ The platform itself is open source | GitHub |
| Self-hosting | ✗ SaaS only | ✓ Self-host anywhere (single binary or Helm) or use OpenObserve Cloud | Learn more |
| Pricing model | Per GB ingested per day, rate increases with hot retention tier | Simple ingest-based pricing; retention doesn't multiply your rate | Pricing |
| Long-term retention | Short hot retention (days); older data moves to cold/archive tiers | Months or years on object storage, always queryable | Learn more |
| Storage backend | Managed OpenSearch + metrics store in vendor's cloud | Your own object storage (S3, GCS, Azure Blob) in Apache Parquet | Architecture |
| Architecture | Separate subsystems: OpenSearch (logs), Prometheus/M3 (metrics), Jaeger (traces) | Single unified engine for all telemetry signals | Learn more |
| Query language | Lucene / OpenSearch DSL for logs, PromQL for metrics | SQL for logs and traces, PromQL for metrics | Used universally with no learning curve |
| OpenTelemetry support | ✓ OTel-based collector and integrations | ✓ OTel-native: OTLP for logs, metrics, and traces | OpenTelemetry |
| Data ownership | Data lives in Logz.io's cloud | Your data, your bucket, open format — no exit friction | Learn more |
| IAM & SSO | ✓ | ✓ | SAML, OIDC, LDAP, role-based access |
Migrating from Logz.io
Because Logz.io's shipping is already OpenTelemetry-based, migration is mostly an endpoint change — not a re-instrumentation project.
Re-point your OpenTelemetry collectors
Logz.io's Telemetry Collector is built on the OTel Collector. Swap the Logz.io exporter for OpenObserve's OTLP endpoint and dual-ship to both platforms during the transition. No code or instrumentation changes required.
Recreate dashboards and migrate alerts
Translate your Lucene/OpenSearch log queries to SQL — your PromQL metrics queries work as-is. Rebuild key dashboards in OpenObserve's modern UI and configure alerts with equal or better granularity.
Cut over and extend your retention
Gradually shift production workloads from Logz.io, starting with non-critical services. Once cut over, extend retention to months on object storage — without tiering fees. 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."
Frequently Asked Questions
Common questions about switching from Logz.io to OpenObserve
Yes, especially if you chose Logz.io for its open-standards approach. Both platforms are OpenTelemetry-friendly and cover logs, metrics, and traces. The difference: OpenObserve is open source itself (not just built on open source), can be self-hosted anywhere, and stores data on object storage — so long retention doesn't multiply your bill the way Logz.io's retention-tier pricing does.
Logz.io charges per GB ingested per day, and your per-GB rate increases with the hot retention tier you choose — so keeping logs searchable for 30 days costs meaningfully more per GB than 7 days. Metrics and traces are billed separately. OpenObserve's pricing is ingest-based and retention lives on cheap object storage, so keeping data for months doesn't inflate your rate. Teams with high volumes or long retention needs typically see the biggest savings.
Easier than most migrations. Logz.io's shipping is OpenTelemetry-based, so you typically just re-point your OTel Collectors (or Fluent Bit/Fluentd agents) to OpenObserve's OTLP/HTTP endpoints — no re-instrumentation. The main work is translating Lucene/OpenSearch log queries to SQL and rebuilding dashboards; PromQL metrics queries carry over as-is. Most teams run both platforms in parallel for a few weeks, then cut over.
Logz.io is a polished managed service with strong onboarding, a mature Kibana/OpenSearch experience, and a dedicated Cloud SIEM product. If you rely heavily on its SIEM correlation rules, evaluate that gap carefully. For core observability — logs, metrics, traces, dashboards, alerts, and pipelines — OpenObserve matches or exceeds it, with a single engine instead of three stitched-together stacks, plus VRL-based pipelines for transformation and redaction.
Yes. OpenObserve is open source and runs as a single binary for small setups or as a horizontally scalable HA cluster via Helm on Kubernetes. You can keep all telemetry in your own S3/GCS/Azure bucket — useful for data-residency, compliance, or air-gapped requirements that a SaaS-only platform can't meet. A managed OpenObserve Cloud is also available if you prefer not to operate it.
This is where the models differ most. On Logz.io, hot retention is measured in days, and older data moves to cold/archive tiers with restrictions on how you query it. OpenObserve stores everything as compressed Parquet on object storage, so 6 or 12+ months of retention stays affordable and directly queryable with SQL — no rehydration step.
Yes. OpenObserve is SOC2 Type II certified and ISO 27001 compliant. We process over 2 PB of data daily across thousands of deployments, including Fortune 100 enterprises. Enterprise features include RBAC, SSO, sensitive data redaction, and dedicated support.
OpenObserve: the open-source Logz.io alternative
The open-standards observability you wanted from Logz.io — but open source, self-hostable, and built on object storage with 140x lower storage costs than OpenSearch-style indexing. Long retention without tiering fees. Also evaluating other tools? See how OpenObserve compares to Elasticsearch, Coralogix, Sumo Logic.
- 140x lower storage cost vs. OpenSearch-style indexing
- Months of retention — no hot/cold tiering fees
- Open source, OTel-native — self-host or cloud