Data Engineering

Real-Time Streaming

Batch processing is not fast enough for fraud detection, live personalization, or operational monitoring. We design and build streaming architectures that process events in milliseconds, deliver data to dashboards in seconds, and handle failures without losing events.

<100ms

End-to-End Latency

1M+

Events Per Second

99.99%

Zero Message Loss

What We Deliver

Real-Time Streaming Services

Practical, production-ready work — not proofs of concept that never make it to real users.

Kafka Architecture

Apache Kafka cluster design, topic modeling, consumer group management, and schema registry for enterprise event streaming.

Stream Processing

Apache Flink and Spark Streaming jobs for real-time aggregations, joins, enrichment, and windowed computation.

CDC Integration

Change data capture from relational databases using Debezium to stream row-level changes into your data platform.

Real-Time Analytics

Live dashboards and alerting on streaming data using Apache Druid, ClickHouse, or real-time views in your data warehouse.

How We Engage

Common Engagements

01

Fraud Detection

Real-time transaction scoring pipeline that evaluates fraud risk within milliseconds of transaction initiation.

02

Live Operations Dashboard

Streaming aggregation pipeline that feeds an operational dashboard with metrics updating every few seconds.

03

Event-Driven Microservices

Kafka-based messaging backbone connecting microservices with durable event delivery and consumer group management.

04

IoT Data Ingestion

High-throughput ingestion of sensor and telemetry data from connected devices into a processing and storage platform.

Why InnovTen

What You Can Count On

  • At-least-once and exactly-once delivery guarantees depending on your use case requirements
  • Schema registry integration that prevents consumer breakage from upstream schema changes
  • Backpressure handling that degrades gracefully under load spikes
  • Replay capability for reprocessing historical events through updated logic
  • Operational runbooks and on-call escalation procedures delivered with every streaming system

Technologies We Use

Apache Kafka Apache Flink Spark Streaming Debezium Confluent Cloud AWS Kinesis Apache Druid ClickHouse

Ready to Get Started?

Tell us about your project and we'll put together a practical path forward.

Talk to Our Team