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Geospatial System Architecture | Bikash Sapkota

Architecture patterns for GPS-scale ingestion, spatial enrichment, feature marts, ClickHouse serving, maps, APIs, and analytics outputs.

Mobility Data Lakehouse: A reusable pattern for turning high-volume GPS data into analytics-ready spatial features and product outputs.

Flow: Sources -> Kafka / batch ingest -> S3 raw zone -> Spark + Glue -> H3 feature marts -> ClickHouse / APIs

Principles: Schema contracts, Partition-aware processing, Spatial indexing, Cost-aware compute, Observable outputs

Geospatial Product Layer: A serving layer designed for teams that need fast comparison across movement metrics, time windows, and geographic cells.

Flow: Feature tables -> Aggregation jobs -> ClickHouse -> Map tiles / CSV -> Dashboards -> Decision workflows

Principles: Low-latency reads, Reproducible exports, Map-ready geometry, Clear lineage, Stakeholder trust