SaaS platforms whose customer-facing analytics dashboards time out on standard OLTP tables frequently search to hire a freelance ClickHouse, DuckDB & TimescaleDB real-time analytics programmer. I am Aldian Fazrihady, a Senior Freelance Backend & Data Engineer available via Upwork.
Core Columnar & Time-Series Database Capabilities
- ClickHouse OLAP Architecture: Designing `MergeTree` / `ReplacingMergeTree` ordering keys, incremental materialized views, and Kafka/CDC ingestion pipelines that aggregate billions of event rows in under 50 milliseconds.
- TimescaleDB on PostgreSQL: Implementing automated time-partitioned hypertables, columnar compression (90%+ storage savings), and continuous aggregates inside your existing PostgreSQL ecosystem.
- In-Process DuckDB & Parquet Pipelines: Querying S3/GCS Parquet lakes directly via DuckDB in Python or Node.js for lightning-fast zero-warehouse reporting.
Frequently Asked Questions
When should we use TimescaleDB vs. ClickHouse?
TimescaleDB is ideal when you want relational joins with existing PostgreSQL tables and up to hundreds of millions of time-series rows; ClickHouse excels at multi-billion-row high-cardinality event analytics and observability workloads.
How can we hire you for ClickHouse, DuckDB, or TimescaleDB engineering?
Message me on Upwork.