Companies that use Kafka Streams
It is a client library for building applications and microservices, where the input and output data are stored in Kafka clusters. It combines the simplicity of writing and deploying standard Java and Scala applications on the client side with the benefits of Kafka's server-side cluster technology.
3,706
companies
List of companies using Kafka Streams
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is any of
Kafka Streams
Employees370Marketing ServicesKafka StreamsHigh confidence
Employees1.1kRevenue$256MSoftware DevelopmentKafka StreamsHigh confidence
Employees355Software DevelopmentKafka StreamsHigh confidence
Employees107Revenue$30MSoftware DevelopmentKafka StreamsHigh confidence
Employees619Software DevelopmentKafka StreamsHigh confidence
Employees180ConstructionKafka StreamsHigh confidence
Employees231Revenue$3.5MSoftware DevelopmentKafka StreamsHigh confidence
Employees8.5kRevenue$71MInsuranceKafka StreamsHigh confidence
Employees169Technology, Information and InternetKafka StreamsHigh confidence
Employees1.8kRevenue$32MSoftware DevelopmentKafka StreamsHigh confidence
We have data on 3,706 companies and users that use Kafka Streams. Our Kafka Streams users and customers list is available for download and comes enriched with vital company specifics, including industry classification, organizational size, geographical location, funding rounds, and revenue figures, among others.
Technology Usage Statistics and Market Share
How to target Kafka Streams users
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Frequently asked questions
Our data is sourced from job postings collected from millions of companies. We monitor these postings on company websites, job boards, and other recruitment platforms. Analyzing job postings provides a reliable method to understand the technologies companies are employing, including their use of internal tools.
We refresh our data daily to ensure you are accessing the most current information available. This frequent updating process guarantees that our insights and intelligence reflect the latest developments and trends within the industry.
Kafka Streams is a powerful technology that enables developers to build custom applications and microservices with real-time data processing capabilities. It is an open-source stream processing library that is part of the Apache Kafka project. With Kafka Streams, developers can easily transform and manipulate data streams in real-time, allowing for efficient and scalable processing of data within their applications.
Stream Processing is the category to which Kafka Streams belongs, focusing on the processing and analysis of continuous data streams. In essence, Stream Processing involves the handling of data as it is generated, providing businesses with the ability to react quickly to changing data and make informed decisions in real-time. Kafka Streams specifically enables users to perform tasks such as data filtering, aggregation, and joining across various streams, all while ensuring fault tolerance and scalability.
Kafka Streams was founded in 2016 as part of the Apache Kafka project, driven by the need for a high-performance, fault-tolerant stream processing solution that seamlessly integrates with the Kafka messaging system. Its inception aimed to empower developers to leverage the power of Kafka for building robust stream processing applications without the need for external dependencies. Since then, Kafka Streams has gained significant traction in the data processing landscape, becoming a go-to choice for companies seeking real-time data processing capabilities.
Currently, Kafka Streams holds a substantial market share within the Stream Processing category, with many organizations adopting it for their real-time data processing needs. The technology's seamless integration with Apache Kafka, coupled with its robust feature set and scalability, positions Kafka Streams for continued growth in the future. As the demand for real-time data processing solutions increases across industries, it is likely that Kafka Streams will continue to expand its market share and solidify its presence as a leading stream processing technology.