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Comparing Dedicated Columnar Engines with Relational Hypertables
When ingesting millions of telemetry metrics per minute from IoT sensors, server agents, or financial tickers, choosing the right time-series database is critical. TimescaleDB extends PostgreSQL with automated chunking (Hypertables) and full ACID compliance, while ClickHouse utilizes vectorized columnar storage designed for blazing-fast analytical aggregations.
Documented by Saizul Amin based on 100M-row synthetic IoT telemetry benchmark runs.
Benchmark Summary (16-core Bare Metal, NVMe Storage)
| Metric | TimescaleDB (PostgreSQL 16) | ClickHouse 24.3 |
|---|---|---|
| Ingestion Throughput | 210,000 rows/sec | 1,450,000 rows/sec (7x Faster) |
| Data Compression Ratio | 5.2x (Native Compression) | 9.8x (Columnar LZ4/ZSTD) |
| Complex Aggregation Latency | 180ms | 14ms (12x Faster) |
| ACID Relational Joins | Full PostgreSQL Ecosystem | Limited / Denormalized Preferred |
Md Saizul Amin
Digital Systems Strategist · AI Agent Developer · 9+ years in digital & ITMd Saizul Amin is a digital systems strategist and AI automation engineer from Dhaka, Bangladesh. With 9+ years across IT, web development and digital marketing, he writes practical guides on technology, business, education and online growth — and builds the same kinds of systems (AI agents, websites, SEO and ad campaigns) for clients in Bangladesh, the UK and the USA.
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Credentials & experience
- 🎓B.Sc. in Computer Science & EngineeringBangladesh University of Business & Technology (BUBT), 2017–2021
- 🤖AI Automation Engineer · Web Developer · SEO SpecialistUnique Mark Limited, Birmingham UK — 2024 to present
- 🌱IT SpecialistGreen Fund Initiative Inc., USA — 2024 to present
- 🏥Junior IT Consultant — Ministry of Health (DGHS)Built the first national Shareable Health Record website; supported 6,000+ facilities
- 🧭Head of ITWEDO Bangladesh — led IT for 50+ staff, 2021–2023