Built for petabyte-scale search
Stop waiting on indexed searches. Orbital queries raw log data in real-time without the overhead of Elastic or Splunk.
Analyzing petabytes at
Infrastructure Specs
We bypassed the JVM and built our index on bare metal to eliminate GC pauses and latency spikes.
Distributed keyword search across your entire historical footprint without waiting for index warming.
Send raw JSON or structured logs. Our engine infer types at query time to prevent pipeline bottlenecks.
Define access policies based on log metadata. Keep PII restricted while allowing engineers to debug production.
Stream production logs to your terminal with a CLI that supports standard unix pipes and filters.
Query S3 or GCS buckets directly. No re-hydrating data or paying for idle compute cycles.
Skip proprietary query languages. Use standard SQL joins and aggregations to correlate logs across services.
How it works
Most teams have working focus rules within 24 hours of connecting their calendar.
OAuth in 10 seconds. Helix imports your calendar, reads the patterns, proposes rules.
Set hours, days, project types. Helix builds the policy; you tune it. Edit any time.
Protections fire automatically. You get a daily brief. Nothing else changes about your calendar UX.
From the front lines
Direct feedback from backend teams handling 50TB+ of daily ingest.
We replaced a sprawling Elasticsearch cluster with a single Orbital instance. Query latency dropped from seconds to milliseconds without changing our schema.
Most tools choke on petabyte-scale cardinality. Orbital is the first engine I’ve used that handles high-dimension metadata without spiking our cloud bill.
The regex performance is actually what they claim. We run complex pattern matches across week-long datasets in under three seconds.
Deployment took twenty minutes. We pointed our collectors at the endpoint and immediately saw more reliable indexing than our previous managed provider.
Orbital’s decoupled storage means we don't have to scale compute just because our log retention grew. It saved us 40% on infra costs in Q1.
Finally, a log tool that doesn't feel like it was built in 2012. The CLI is fast, the API is predictable, and it just works at scale.
Search petabytes of data with sub-second latency. No indexing delays, no storage tiers, no hidden costs.