Massive-Scale Logging
ClickHouse: Lightning-Fast Analytics for Logs & Spans
Stop waiting for your log queries to finish. ClickHouse provides sub-second query performance on petabytes of data, serving as the ultimate backend for OTel logs and traces.
Why ClickHouse for Observability?
The engine powering the world's most demanding telemetry pipelines.
Columnar storage allows you to filter billions of logs in milliseconds without complex indexing.
Advanced codecs (ZSTD, Delta) reduce log storage footprints by up to 15x compared to Elasticsearch.
Use standard SQL to join logs with traces or business data for deeper root-cause analysis.
Unified Log & Trace Storage
Eliminate tool sprawl. We build unified backends where logs and spans live together, enabling seamless correlation during outages.
- →Linear Scaling: Add nodes to your cluster to increase both storage and query throughput.
- →Native OTel Integration: Direct ingestion via the OpenTelemetry ClickHouse exporter.
The ClickHouse Path
Moving away from Elastic or Splunk? Our migration plan focuses on schema optimization and cost reduction from day one.
Schema-on-Write Power
ClickHouse tables are optimized for OTel's nested attributes. By structuring data correctly at ingestion, we eliminate the "slow search" problem forever.
- ✓ Integrated Bloom filters for fast lookups
- ✓ JSON attribute flattening for SQL access
- ✓ Tiered storage (SSD to S3) support
// OTel Logs Table Example
CREATE TABLE otel_logs (
Timestamp DateTime64(9),
TraceId String,
SpanId String,
SeverityText LowCardinality(String),
Body String,
ResourceAttributes Map(String, String),
LogAttributes Map(String, String)
) ENGINE = MergeTree()
ORDER BY (SeverityText, Timestamp);
Your Logs, Faster than Ever
Reduce your logging spend by 70% while improving query speed. Book a ClickHouse architecture session.