OpenObserve vs Elasticsearch

For observability — logs, metrics, and traces — yes. OpenObserve was built specifically as an ELK replacement: it ships logs to compressed columnar Parquet on object storage (about 140x lower storage cost in our benchmark), needs no index, shard, or JVM management, and includes dashboards, alerts, and pipelines out of the box. If you use Elasticsearch as a general-purpose search engine or document store for your product, that is Elasticsearch's home turf — keep it there and move only your observability workloads.

Two savings compound. Storage: Elasticsearch indices are often as large as the raw data and then replicated across hot nodes, while OpenObserve compresses data into Parquet on S3 — roughly 140x lower storage cost in our published benchmark. Operations: no dedicated cluster to size, tier, and babysit. If you are on Elastic Cloud, you are also billed per GB for ingest and retention (measured on uncompressed data), which grows linearly with volume. Actual savings depend on your data shape, replication factor, and retention.

Easier than most migrations, because it is a pipeline cutover rather than a data migration. OpenObserve exposes an Elasticsearch-compatible API, so Filebeat, Fluent Bit, Logstash, and the OpenTelemetry Collector can dual-ship with an output-endpoint change. Run both platforms in parallel for a few weeks, rebuild your critical Kibana dashboards in SQL, then let old indices age out. Simple setups cut over in days; larger estates with heavy Logstash logic typically take a few weeks to a couple of months.

Elasticsearch's inverted index is best-in-class for general-purpose document search, and we won't pretend otherwise. OpenObserve provides full-text search designed for observability workloads — finding errors, request IDs, and patterns across huge log volumes — plus SQL for structured analysis. For log exploration and troubleshooting, teams rarely miss anything. For powering product search features, Elasticsearch remains the right tool.

No. There are no shards to size, no ILM policies to write, no index mappings to fight, and no JVM heap to tune. OpenObserve is a single Rust binary (or a stateless HA cluster via Helm) with data on object storage, so a node restart doesn't trigger shard-recovery storms and there are no garbage-collection pauses or OutOfMemory crashes to chase.

Yes. The core platform is open source on GitHub (19k+ stars) and you can self-host it anywhere — a laptop, a VM, or Kubernetes — with your own S3-compatible bucket, so your data stays under your control. A managed cloud offering and enterprise features (advanced RBAC, SSO, support) are available when you want them.

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.