Apache Kafka & Real-Time Streaming Implementation Partner — Bengaluru, India

Confluent Cloud is ideal for teams that want managed infrastructure with minimal ops overhead. Self-managed Kafka (on Kubernetes with Strimzi) gives you more control and can be cheaper at scale. We help you evaluate based on your team size, traffic volume, compliance requirements, and budget.

Kafka is designed for high-throughput, ordered event streaming with replay capability — ideal for event sourcing, log aggregation, and real-time analytics. RabbitMQ is better for traditional message queuing with complex routing. SQS is simplest for basic async processing. We recommend Kafka when you need event replay, high throughput, or stream processing.

Kafka handles millions of messages per second in production at companies like LinkedIn, Uber, and Netflix. The key is proper cluster sizing, partition strategy, and consumer group design. We benchmark against your expected throughput and design for 3-5x headroom.

A basic Kafka cluster with 2-3 producer/consumer services takes 3-4 weeks. A full event-driven architecture with stream processing, schema management, monitoring, and multi-service integration typically takes 8-14 weeks depending on the number of services and data sources.

Yes. Redpanda is a Kafka-compatible alternative written in C++ that offers lower latency and simpler operations. Apache Pulsar provides multi-tenancy and geo-replication natively. We evaluate your requirements and recommend the best fit — we're not locked into any single platform.