Apache Flink for Robust Data Stream Management

From real-time analytics to fraud detection to personalized streaming, Flink delivers the building blocks required by your future-proof application.

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  • Stream Without Limit

    Build systems that compute over data as it's created. Apache Flink powers ultra-low-latency, high-throughput pipelines that can easily handle both unbounded streams and bounded (batch) data sets, so your insights keep flowing.

  • State at Scale

    Flink's strong state management and exactly-once semantics ensure your data processing is reliable, accurate, and consistent - even in fault conditions. From event-time processing through late or out-of-order data, your system stays correct.

  • One Engine, Dual Power

    Why do you need to choose stream or batch? Flink does both. One architecture and API cover real-time streams and batch processing, optimized under the hood for whatever data you provide - without requiring additional tooling.

  • Recover Fast, Stay Resilient

    Ingrained checkpointing and savepoints let Flink programs recover gracefully from crashes - or suspend and resume right where they left off. No data loss, no getting your bearings.

  • Connect Everywhere

    Flink integrates seamlessly with Kafka, Cassandra, HDFS, S3, Elasticsearch, or more. Pipe things together from here to there.

  • Future-Ready with Community Momentum

    Flink is open-source and backed by an active community and the Apache Software Foundation. With over a decade of live development, it's been battle-tested and remains in constant development.

  • Industry-Proven Reliability

    Benchmarks expose Flink as a leader in fault recovery and stability among streaming frameworks. Flink is easily resilient to disorder, ensuring your data pipeline is rock-solid.

VP of Engineering
Health analytics company

"SoftwareMill consistently provides communicative, skilled resources who are able to work within the business' tech stack and produce high-quality products, which has been advantageous."

Kamil "Rudy" Dobrzyński
Head of Engineering, Uncapped

"The team members have deep expertise in multiple areas so they really contributed to the overall shape of the product."

Leonardo Taccari
Cloud Architect, faire.ai

"SoftwareMill worked with us to quickly bring up infrastructure in our very early stage for multiple environments on multiple AWS accounts based on Kubernetes. After several years we ended up in a disaster and accidentally lost several Kubernetes namespaces. It was a pleasure to be able to restore the namespace in literally a couple of minutes!"

Daniel Pfeiffer
VP of Engineering, Firstbird

"Thanks to the SoftwareMill team, the company was able to improve their technical foundation, making maintenance a much easier process moving forward. As a result, they are able to meet their customer's functionality requirements."

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+15 years of commercial experience
+7 avg. project duration in years
  • 1. What is Apache Flink used for?

    Apache Flink is a distributed stream processing platform for analyzing and responding to data in real time. It's used for applications like fraud detection, anomaly detection, real-time analytics, personalized recommendations, and monitoring systems where low latency and accuracy matter.

  • 2. Is Flink limited to streaming data?

    No. Flink is best known for real-time stream processing, but it also supports batch workloads with the same APIs and runtime. This one-framework approach lets you work with bounded datasets and unbounded streams without switching frameworks.

  • 3. How does Flink provide reliability?

    Flink provides exactly-once semantics through checkpointing and savepoints, so your data remains correct and consistent even when the system fails. It can resume to its exact state when it was interrupted.

  • 4. Can Flink scale to very large workloads?

    Yes. Flink is designed to run across clusters and cloud environments and scale out to enable extremely high throughput and massive state sizes. Every day, Flink-using enterprises handle billions of events.

  • 5. What does Flink integrate with?

    Flink integrates with many large data sources and sinks through connectors, including Apache Kafka, Cassandra, HDFS, S3, Elasticsearch, and JDBC databases. It allows for straightforward embedding into existing data infrastructure.

  • 6. Is Apache Flink cloud-native?

    Yes. Flink can be run on bare metal, VMs, Kubernetes, or fully managed cloud providers. Its elastic scalability and distributed architecture make it perfect for modern hybrid and cloud-native environments.