HyperDX is a ClickHouse-powered observability platform emphasizing fast search, correlated session replay, and automatic log pattern clustering, priced by…
Best for HyperDX: Teams wanting ClickHouse-backed, terabyte-scale log and trace search with correlated session replay and automatic pattern clustering, on a flat monthly storage plan starting at $20/month with unlimited users.
Best for OpenObserve: Teams wanting a unified logs/metrics/traces/RUM platform with AI-assisted natural-language queries and root-cause analysis, either self-hosted free up to 50 GB/day or on Cloud at usage-based per-GB pricing.
At a Glance
HyperDX
OpenObserve
Primary category
DevOps
DevOps
Rating
Not documented
Not documented
Pricing model
Freemium
Freemium
Starting price
Free; Starter from $20/month (50 GB included)
Free (self-hosted open source); Cloud from $0.50/GB ingested
Free plan
Yes
Yes
Free trial
Yes
Yes
Platforms
Web
Web
Team collaboration
Not documented
Not documented
AI features
Not documented
Yes
Public API
Yes
Yes
Key Differences
Underlying Data Engine
HyperDX: HyperDX is explicitly ClickHouse-powered, built for searching terabytes of events in seconds, and was later acquired by ClickHouse itself.
OpenObserve: OpenObserve uses Apache Parquet columnar compression on object storage, optimized for lower storage cost rather than a named high-speed query engine.
Query engine choice affects both search speed at scale and storage cost trade-offs.
Log Pattern Analysis
HyperDX: HyperDX includes Automatic Pattern Clustering, condensing billions of log events into recognizable patterns.
OpenObserve: OpenObserve does not document a comparable automatic log pattern clustering feature.
Pattern clustering helps engineers quickly spot anomalies in massive log volumes without manual filtering.
Pricing Model
HyperDX: HyperDX charges flat monthly tiers by storage volume, $20/month for 50 GB with unlimited users, plus $0.40/GB overage.
OpenObserve: OpenObserve's Cloud plan charges per-GB for both ingestion ($0.50/GB) and query ($0.01/GB) separately.
Flat storage-tier pricing with unlimited users is easier to budget for growing teams than combined ingestion-plus-query metering.
Ownership and Backing
HyperDX: HyperDX was built by Y Combinator-backed DeploySentinel, Inc. and later acquired by ClickHouse, adding stability and resources; it's headquartered in San Francisco.
OpenObserve: OpenObserve does not document VC backing or acquisition history; it's headquartered in Menlo Park, California.
Backing and ownership history can signal long-term product stability and investment.
AI-Assisted Querying
HyperDX: HyperDX does not document AI-powered querying or automated root-cause analysis features.
OpenObserve: OpenObserve includes an AI Assistant and SRE Agent for natural-language queries and automated root-cause analysis on Cloud/Enterprise plans.
AI-assisted querying can reduce the query-language expertise needed to investigate incidents.
Feature-by-Feature
Data Collection & Search
Feature
HyperDX
OpenObserve
ClickHouse-powered query engine
Available
Not documented
End-to-end distributed tracing
Available
Available
Automatic log pattern clustering
Available
Not documented
No-query chart builder
Available
Not documented
OpenTelemetry support
Available
Available
Session & User Monitoring
Feature
HyperDX
OpenObserve
Correlated session replay
Available
Available
Real user monitoring (RUM)
Not documented
Available
Named alert integrations (Slack/email/PagerDuty)
Available
Not documented
Pricing & Compliance
Feature
HyperDX
OpenObserve
Free tier
Available
Available
Paid starting price
Available
Available
AI-assisted querying
Unavailable
Available
SOC 2 certification
Available
Available
Pricing Compared
Starting price reflects the lowest paid tier, not the full cost for every team size or usage level.
HyperDX
Free — $0/month Monthly
Starter — $20/month Monthly
Enterprise — Custom pricing Custom
OpenObserve
Self-Hosted Open Source — Free N/A
Self-Hosted Enterprise — Free up to 50GB/day ingestion N/A
Cloud Professional — $0.50/GB ingestion, $0.01/GB query Pay as you go
Cloud Enterprise — Custom Custom
Pros & Cons
HyperDX
Pros
Fully open source and self-hostable under MIT and Apache 2.0 licenses
ClickHouse backend delivers fast queries even at very large log and trace volumes
Usage-based pricing avoids expensive per-seat or per-host costs common at competitors
Unifies logs, traces, metrics, and session replay in one interface instead of separate tools
Backed by ClickHouse Inc.'s engineering resources following the 2025 acquisition
Cons
Newer platform with a smaller overall feature set than mature vendors like Datadog or New Relic
Self-hosting requires operating and maintaining a ClickHouse cluster
Free tier retention is limited to just 3 days, which may be too short for some teams
Documentation and ecosystem are still maturing following the ClickHouse acquisition
Fewer pre-built third-party integrations than long-established observability vendors
OpenObserve
Pros
Significantly lower storage costs than Elasticsearch or Datadog
Unifies logs, metrics, traces, and RUM in a single platform
Generous free self-hosted Enterprise tier up to 50GB per day
Backed by a strong Series A and adoption from Fortune 100 companies
Simple, transparent cloud pricing with no per-seat charges
Cons
Younger platform with a less mature ecosystem than Elastic or Datadog
Advanced AI features are still in preview
Enterprise features like SSO and audit trail require a paid tier at scale
Smaller third-party integration marketplace than established APM vendors
Choose HyperDX: Teams wanting ClickHouse-backed, terabyte-scale log and trace search with correlated session replay and automatic pattern clustering, on a flat monthly storage plan starting at $20/month with unlimited users.
Choose OpenObserve: Teams wanting a unified logs/metrics/traces/RUM platform with AI-assisted natural-language queries and root-cause analysis, either self-hosted free up to 50 GB/day or on Cloud at usage-based per-GB pricing.
Need both: There isn't a strong case for running both together; they overlap almost entirely as open-source, OpenTelemetry-compatible, self-hostable observability platforms, so teams would typically standardize on one rather than split telemetry data across two competing systems.
HyperDX
Debugging Production Incidents — Correlate logs, traces, and session replay in one place to quickly find the root cause of an outage.
Self-Hosted Observability on Existing Infrastructure — Run observability entirely on a team's own ClickHouse cluster for cost and data control.
Cost-Sensitive Observability at Scale — Monitor growing data volumes without per-host or per-seat pricing eating into infrastructure budgets.
OpenObserve
Replacing costly Elasticsearch or Datadog stacks — Engineering teams migrate to OpenObserve to cut logging and monitoring storage costs significantly.
AI-assisted incident response — SRE teams use OpenObserve's AI SRE agent and AI assistant to speed up incident detection and root-cause analysis.
Compliance-driven self-hosted observability — Regulated enterprises self-host OpenObserve to keep observability data in-house while meeting audit trail and access control requirements.
Frequently Asked Questions
Which platform uses ClickHouse?
HyperDX is explicitly ClickHouse-powered and was later acquired by ClickHouse. OpenObserve uses its own Parquet-based object storage approach and isn't documented as ClickHouse-based.
Which is cheaper for low-volume use?
HyperDX's free tier gives 3 GB/month with 3-day retention. OpenObserve's Open Source Edition is free with unlimited usage if self-hosted, though its Cloud plan starts at $0.50/GB ingestion.
Does either tool offer AI-assisted querying?
OpenObserve documents an AI Assistant and SRE Agent for natural-language queries and root-cause analysis on Cloud/Enterprise plans. This isn't a documented HyperDX feature.
Are both tools open source?
Yes, both HyperDX and OpenObserve are open source with self-hosted options.
Who owns or backs these companies?
HyperDX was built by Y Combinator-backed DeploySentinel and later acquired by ClickHouse. OpenObserve's ownership and backing aren't documented; it's headquartered in Menlo Park, California.
Which tool has automatic log pattern clustering?
HyperDX documents this explicitly, condensing billions of log events into recognizable patterns. This isn't a documented OpenObserve feature.