About the service
I design fast analytical databases on ClickHouse that answer queries on billions of rows in under a second. Every project starts with a data model: I think through the schema, choose the sort key and partitioning, pick the right engine — MergeTree, ReplacingMergeTree or AggregatingMergeTree — so frequent queries read as little data as possible.
Then I set up data ingestion for your event stream — from a message queue, object storage or database changelog. Batching, deduplication and load control keep inserts cheap and loss-free at peaks, materialized views compute aggregates on write, and TTL separates hot and cold data to where they're cheaper.
Finally I connect everything to dashboards, verify numbers against a reference source and load the system with realistic query concurrency. You get documented schemas, reproducible migrations and clear query templates that your team will extend without me.
What's included:
— Schema, partitioning and sort key tuned for your queries
— Streaming or batch data ingestion with deduplication and monitoring
— Materialized views and TTL for sub-second summaries
Then I set up data ingestion for your event stream — from a message queue, object storage or database changelog. Batching, deduplication and load control keep inserts cheap and loss-free at peaks, materialized views compute aggregates on write, and TTL separates hot and cold data to where they're cheaper.
Finally I connect everything to dashboards, verify numbers against a reference source and load the system with realistic query concurrency. You get documented schemas, reproducible migrations and clear query templates that your team will extend without me.
What's included:
— Schema, partitioning and sort key tuned for your queries
— Streaming or batch data ingestion with deduplication and monitoring
— Materialized views and TTL for sub-second summaries
