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ClickHouse is a columnar analytical database designed for high-performance analytics on large datasets. Where a traditional row-oriented database struggles with analytical queries across millions of rows, ClickHouse executes the same queries in milliseconds — because it stores and reads data by column rather than by row, scanning only the columns required by each query. Hellenic Technologies uses ClickHouse as the analytical data warehouse in client BI implementations where data volume, query performance, or cost at scale are primary requirements. For clients running high-traffic e-commerce sites, large-scale ad operations, or event-driven analytics workloads, ClickHouse delivers query performance that PostgreSQL and BigQuery cannot match at the same cost point. Why ClickHouse:
  • Columnar storage — Queries that aggregate across large numbers of rows read only the columns they need. A query summing revenue across 500 million order rows reads one column, not the entire row set.
  • Petabyte scale — ClickHouse is designed to scale to petabytes of data on commodity hardware. Horizontal scaling is supported through sharding and replication.
  • Sub-second query response — Analytical queries that take minutes in a general-purpose database typically execute in under a second in ClickHouse, enabling real-time dashboard refresh and interactive ad-hoc analysis.
  • Efficient compression — Columnar storage enables aggressive compression of similar values. Data that occupies 1TB in a row-oriented database often compresses to 100-200GB in ClickHouse, reducing storage cost significantly.
  • Materialised views — Frequently-run aggregations can be pre-computed as materialised views, reducing query time to near-instant for dashboards with predictable query patterns.
Our ClickHouse implementations include:
  • Self-hosted ClickHouse deployment on your infrastructure or cloud environment
  • Schema design optimised for your specific query patterns
  • Airbyte pipeline configuration for continuous data ingestion
  • Metabase connection and data model setup
  • Query optimisation and index configuration for dashboard performance