Columnar Analytical Engine
Storing billions of telemetry rows with sub-second aggregate query speeds and high compression ratios.
DATA ANALYTICS & TELEMETRY
Sub-second telemetry & executive BI dashboards.
We engineer real-time data pipelines, ClickHouse time-series storage, and executive Grafana dashboards processing sub-second sensor streams across 45,000+ utility and industrial endpoints.
ANALYTICS SPECS45,000+ ENDPOINTS
Database LayerClickHouse & Redis
ProtocolMQTT / SCADA / REST
VisualizationGrafana BI & React 19
Ingest SLASub-Second Concurrency
Bengaluru Analytics Practice
45,000+High Scale
Active utility endpoints monitored
Sub-SecondReal-Time
MQTT telemetry ingestion latency
100:1 CompressionCost Efficient
ClickHouse columnar data compression
100% IPFull Ownership
Source code and dashboard schemas
01 / ANALYTICS CAPABILITIES
High-concurrency data engineering.
Real-Time Ingestion Bus
Streaming sensor data frames from field devices via EMQX/Mosquitto brokers into fast Redis message queues.
Interactive Spatial & Chart BI
Building custom Grafana and React 19 dashboards with interactive GIS spatial overlays and fault alerts.
02 / DATA PHILOSOPHY
Data is useless unless it enables immediate operational decisions.
We transform raw sensor streams into actionable dashboards with automated threshold alerts and fault isolation.
03 / DATA TOOLCHAIN
Curated data engineering stack.
01 // DATABASES
- ClickHouse (Columnar)
- Redis (In-Memory Queue)
- PostgreSQL (ACID Core)
- TimescaleDB
02 // INGESTION
- MQTT (Mosquitto/EMQX)
- Apache Kafka Streams
- FastAPI Async Ingest
- gRPC Streaming
03 // VISUALIZATION
- Grafana Enterprise BI
- React 19 Custom Dashboards
- Mapbox GIS Overlays
- Chart.js / Recharts
04 // PIPELINES
- Apache Airflow
- dbt (Data Build Tool)
- Python Pandas & Polars
- Parquet Export
04 / PIPELINE WORKFLOW
Our 4-step data architecture lifecycle.
Data Volume Audit
Evaluating message frequency, payload schemas, and storage retention limits.
Columnar Schema Build
Designing partition keys and high-throughput ingestion pipelines.
Grafana & React BI
Building executive dashboards with custom threshold alert rules.
Production Stream
Deploying zero-downtime data pipelines to production servers.
05 / INSPECTABLE CODE
Data Analytics code snippets.
analytics/clickhouse_ingest.py
High-throughput ClickHouse ingest pipeline writing sub-second MQTT telemetry frames for 45,000+ utility endpoints.
1import clickhouse_connect23client = clickhouse_connect.get_client(host='ch.arivu.internal', port=8123)45def persist_telemetry_batch(batch_data: list):6 # Asynchronous high-concurrency time-series insert7 client.insert('telemetry_stream', batch_data, column_names=['endpoint_id', 'value', 'timestamp'])8 return {"status": "persisted", "rows": len(batch_data)}06 / GUARANTEES
Data project guarantees.
100% IP Transfer
Complete SQL schemas, ingestion scripts, and dashboard definitions transferred.
Sub-Second Query SLA
Optimizing database indexes to guarantee sub-second analytical queries.
Upfront Mutual NDA
Protecting sensitive telemetry and operational metrics with formal NDAs.
PRODUCTION PROOF
Civic Infrastructure Telemetry Platform
Monitoring 45,000+ active utility endpoints with ClickHouse time-series storage and interactive GIS spatial map overlays.
INFRASTRUCTURE SPEC45,000+ ENDPOINTS
• ClickHouse Columnar Ingest
• Sub-Second MQTT Broker
• Mapbox GIS Spatial Overlays
• Automated Leak & Fault Detection
07 / DATA FAQS
Questions about data analytics?
How does Arivu process high-frequency telemetry data?
We use lightweight MQTT brokers (EMQX / Mosquitto) to ingest sensor streams into Redis queues, persisting them asynchronously to ClickHouse columnar database for sub-second analytical queries.