Frequently Asked Questions

Question 1

Is OpenObserve a good Logz.io alternative?

Accepted Answer

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.

Question 2

How does OpenObserve pricing compare to Logz.io?

Accepted Answer

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.

Question 3

How hard is it to migrate from Logz.io?

Accepted Answer

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.

Question 4

Will I lose features Logz.io has?

Accepted Answer

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.

Question 5

Can I self-host OpenObserve? Logz.io is SaaS-only.

Accepted Answer

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.

Question 6

What about long retention for compliance or audit logs?

Accepted Answer

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.

Question 7

Is OpenObserve enterprise-ready?

Accepted Answer

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.

Feature	Logz.io	OpenObserve	Reference Links
Feature parity: logs, metrics, traces, dashboards, alerts, pipelines	✓	✓	Logs Metrics Traces Dashboards Alerts Pipelines
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

OpenObserve vs Logz.io

Why teams switch from Logz.io

No Retention-Tier Fees

Costs That Don't Scale With Volume

Actually Open Source

One Engine, Not Three Stacks

SQL Instead of Lucene

Your Data, Your Bucket

See how OpenObserve replaces Logz.io

Feature comparison

Migrating from Logz.io

Re-point your OpenTelemetry collectors

Recreate dashboards and migrate alerts

Cut over and extend your retention