01
Vectorized query execution
Columnar storage and SIMD-vectorized execution that scan very large tables quickly.
Technologies — Databases & storage
ClickHouse real-time columnar analytics engineering
We build real-time analytics platforms on ClickHouse, designed so dashboard queries over billions of rows come back at interactive speed.
Core capabilities
Why we build with ClickHouse
02
Materialized views & AggregatingMergeTree
Pre-aggregating multi-dimensional metrics on write so dashboards render quickly.
03
High-throughput Kafka ingestion
Kafka engine tables feeding materialized views, with at-least-once delivery and deduplication where it matters.
Use cases
Where ClickHouse fits
Product analytics platforms
Self-serve user funnel, retention and event analysis querying billions of historical events.
Financial market tick data
Storing and analyzing high-frequency order book snapshots with heavy compression.
How we staff it
ClickHouse engineers you interview first
Seniority and experience are agreed in the proposal, and you interview every engineer before they start.
Working-hours overlap is agreed for each engagement and written into the statement of work — the shared window, who shifts hours, and how handoffs work outside it.
Technical FAQs
Frequently asked engineering questions
ClickHouse stores data column by column, so similar values sit together and codecs like ZSTD, DoubleDelta and Gorilla compress them well, often several times smaller than the same data stored row by row.
No. ClickHouse is an OLAP (analytics) database optimized for bulk append writes and fast aggregations, not transactional OLTP updates.
Ecosystem
Related technologies
Planning a ClickHouse project?
Tell us about your architecture, backlog and team. We'll reply within one business day with an honest read on whether we can help.