Time-Series Database: Custom Engine Cost & Timeline 2026
5 min read
Time-series data (sensors, metrics, ticks) has different access patterns than general CRUD. A custom engine tuned for append and range scans can cut cost and latency.
Off-the-shelf options (InfluxDB, TimescaleDB, etc.) work well until you hit very high write throughput, strict retention rules, or need to co-locate with other data. A custom engine lets you control compression, retention, and indexing for your exact use case.
- Single workload (e.g. IoT ingestion + last-N queries): USA/Canada $45K–$90K; India ₹18–40 lakh. Timeline 10–14 weeks.
- Multi-tenant metrics platform: USA/Canada $90K–$160K; India ₹40–75 lakh. Timeline 16–24 weeks.
Deliverables usually include the core engine (C++ or similar), client SDKs, deployment and ops docs, and a handover period.
High write volume (millions of points per second), strict p99 latency, or regulatory needs that are easier to meet with a dedicated design. For moderate scale, managed time-series DBs are often enough. At Hendoi we build custom database engines including time-series and metrics layers for USA, Canada, and Chennai. Contact us for a free quote.
Frequently asked questions
For a single workload (e.g. IoT or metrics), expect roughly $45K–$90K in USA/Canada and ₹18–40 lakh in India. Multi-tenant or broader platforms typically run higher; get a [custom quote](/contact).
Use InfluxDB or TimescaleDB first if they meet your scale and features. Consider a custom engine when you need extreme write throughput, custom retention/compression, or tight integration with your existing stack.
You typically get the core engine (C++ or similar), client SDKs (e.g. Python, Go, Node), deployment and ops documentation, and a handover period. [Hendoi](/services/custom-database-engine-development) includes this for USA, Canada, and India clients. 📞 +91-9677261485 | 📧 support@hendoi.in | [Contact us](/contact)
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