We build with Apache Kafka
We use Apache Kafka to build real-time event streaming pipelines, microservice communication layers, and data integration systems that support your business goals. From topic and partition design to consumer scaling and monitoring, we create products designed to evolve with your needs.
DISCUSS YOUR PROJECTEvent Streaming Core
We move high volumes of events with low latency.
Durable Message Log
We retain event history so consumers can replay data.
Fault-Tolerant Scale
We replicate partitioned topics across brokers for reliability.
BENEFITS OF APACHE KAFKA technology
We use Apache Kafka to stream events in real time, decouple services, and scale data pipelines reliably.
BUILD
[01]- Design topic schemas
- Configure partitions and replicas
- Set up Kafka Connect pipelines
- Define data contracts
ENGAGE
[02]- Stream events in real time
- Process data with Kafka Streams
- Support multiple consumers
- Enable event replay
GROW
[03]- Scale brokers horizontally
- Add new topic partitions
- Extend with new connectors
- Optimize retention policies
Our Apache Kafka Technology Stack
We combine Apache Kafka with Kafka Streams, ksqlDB, Schema Registry, and Kafka Connect for stream processing, data contracts, and integration with your existing databases and services.
Custom Apache Kafka development company
With our Apache Kafka development services, we build real-time event streaming platforms, data pipelines, and event-driven microservices architectures, tailored to your boldest business goals. Having years of experience with Kafka, our engineers harness its full potential to deliver high-throughput, fault-tolerant systems across industries and company sizes. Whether it's building a new streaming backbone or modernizing legacy batch pipelines into event-driven architectures, we design topic structures and processing flows that scale with your product. Our range of Apache Kafka development services spans consulting, architecture design, development, and ongoing maintenance. We work as your technical partner and ensure complete transparency and comfortable communication throughout the process, bringing deep streaming expertise and a pragmatic approach to data pipeline design and problem-solving. All this to make sure your systems stay reliable and responsive as event volume grows, and moves your business forward.
OUR APACHE KAFKA SERVICES
We build, modernize, and support Apache Kafka pipelines around your product goals.
We Turn Technology Into Results
Partner with a team that blends technical precision, creative design, and business insight. We’ll help you launch, scale, and dominate your digital niche.

Frequently Asked Questions
Common questions about how we use Apache Kafka and what it can bring to your project. Have a specific requirement?
How does SoftDoes use Apache Kafka?
We use Apache Kafka to build real-time event streaming platforms, data pipelines, and event-driven microservices architectures. We design topic structures and partitioning strategies around your throughput and consumer requirements.
What types of systems do you build with Kafka?
We build event-driven microservices, real-time analytics pipelines, log aggregation systems, and change-data-capture integrations between databases and downstream applications.
Can Kafka integrate with our existing systems?
Yes. Kafka Connect provides connectors for most databases, message queues, and external services, so Kafka can sit alongside your existing infrastructure without requiring a full rewrite.
Do you work with Kafka Streams and ksqlDB?
Yes, we use Kafka Streams and ksqlDB when a project needs in-stream transformations, aggregations, or real-time analytics without standing up a separate processing cluster.
When do you pair Kafka with Flink or Spark Streaming?
We add Flink or Spark Streaming when a workload needs complex stateful processing, windowed aggregations, or higher throughput than Kafka Streams alone can handle efficiently.
Can you modernize an existing messaging system with Kafka?
Yes. We can migrate a legacy queue or batch pipeline to Kafka gradually, topic by topic, or rebuild it from scratch, depending on your timeline and current architecture.
How do you decide whether Kafka fits a project?
We look at your event volume, latency requirements, existing infrastructure, and team experience, then confirm Kafka is the right fit before starting development.


































