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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.
1,476
aziende
Abbiamo dati su 1,476 aziende che usano Kafka Streams. La nostra lista di clienti Kafka Streams è disponibile per il download ed è arricchita con specifiche vitali dell'azienda, incluse classificazione industriale, dimensioni organizzative, posizione geografica, round di finanziamenti e cifre di ricavi, tra gli altri.
Azienda | Paese | Settore | Dipendenti | Entrate |
---|---|---|---|---|
Purple Drive Technologies | Stati Uniti | It Services And It Consulting | 120 | |
Vectron Systems AG | Germania | It Services And It Consulting | 76 | $30M |
Options Clearing Corporation | Stati Uniti | Financial Services | 2.3K | $577M |
APPIC Solutions LLC | Stati Uniti | It Services And It Consulting | 20 | |
inserve GmbH | Venezuela | It Services And It Consulting | 180 | |
![]() DoubleVerify | Stati Uniti | Advertising Services | 1.2K | |
Dice | Stati Uniti | Software Development | 736 | $12M |
Standard Chartered | Regno Unito | Banking | 85K | $16B |
Experian | Stati Uniti | Information Services | 23K | |
Optum | Stati Uniti | Hospitals And Health Care | 83K | |
Visa | Stati Uniti | It Services And It Consulting | 26K | $31B |
Adevinta Group | Spagna | Online Audio And Video Media | 5K | $932M |
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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.
Stream processing has revolutionized the way businesses handle data in real-time, and Kafka Streams stands out as a prominent player in this field. Companies leverage Kafka Streams for its robust capabilities in processing and analyzing continuous streams of data efficiently. The technology offers a plethora of benefits that set it apart from other similar technologies.
Real-time Data Processing: Kafka Streams excels in real-time data processing, enabling companies to analyze and react to data as it flows through the system. Unlike batch processing technologies, Kafka Streams provides instant insights, allowing businesses to make timely decisions based on up-to-date information.
Scalability and Fault Tolerance: Kafka Streams offers seamless scalability and fault tolerance, ensuring that data processing remains uninterrupted even in the face of failures or spikes in data volume. This resilience makes it a preferred choice for companies looking to maintain consistent performance under various conditions.
Ease of Integration: Kafka Streams seamlessly integrates with other components of the Kafka ecosystem, making it easy for companies to build end-to-end data processing pipelines without facing compatibility issues. This integration simplifies the development process and accelerates time-to-market for new data applications.
State Management: Kafka Streams provides built-in support for state management, allowing companies to maintain and query stateful data within the stream processing application itself. This eliminates the need for external databases, reducing complexity and enhancing overall data processing efficiency.
Community Support and Ecosystem: Kafka Streams benefits from a vibrant community and a rich ecosystem of tools and libraries, providing companies with resources to troubleshoot issues, explore new functionalities, and extend the capabilities of their data processing systems. This robust support network ensures that companies can leverage Kafka Streams to its full potential.
Overall, Kafka Streams offers a comprehensive solution for stream processing that combines speed, reliability, flexibility, and community support, making it a top choice for companies seeking to harness the power of real-time data processing effectively.
Kafka Streams is a popular stream processing technology used by various companies across different industries to analyze real-time data and streamline their operations. Some well-known companies that leverage Kafka Streams in their tech stack include LinkedIn, Netflix, and Uber.
LinkedIn: LinkedIn, the world's largest professional networking platform, utilizes Kafka Streams to process and analyze user interactions in real-time. By implementing Kafka Streams, LinkedIn is able to enhance its recommendation system, personalize user experiences, and improve the overall engagement on the platform. LinkedIn started using Kafka Streams in 2016 as part of its efforts to optimize data processing pipelines and deliver more personalized content to its users.
Netflix: Netflix, a leading streaming service provider, relies on Kafka Streams for real-time data processing to enhance content recommendation algorithms and improve streaming quality for its global audience. By leveraging Kafka Streams, Netflix can dynamically adjust content recommendations based on user behavior and preferences, leading to higher viewer satisfaction and increased retention rates. Netflix integrated Kafka Streams into its tech infrastructure in 2017 to handle the massive amounts of streaming data generated daily and ensure seamless viewer experiences.
Uber: Uber, a pioneering ride-hailing company, employs Kafka Streams for real-time analytics and data processing to optimize its transportation services and enhance the overall user experience. Through Kafka Streams, Uber can efficiently process location data, manage ride requests, and dynamically adjust pricing algorithms to meet the demand in different regions. Uber adopted Kafka Streams in 2015 to handle the growing volume of real-time data generated by millions of users worldwide and improve the responsiveness of its platform.
These case studies highlight how established companies like LinkedIn, Netflix, and Uber have successfully integrated Kafka Streams into their tech infrastructure to drive innovation, improve operational efficiency, and deliver personalized experiences to their users. By harnessing the power of Kafka Streams for stream processing, these companies have been able to stay ahead in their respective industries and leverage real-time data insights to make informed business decisions.
Puoi accedere a un elenco aggiornato di aziende che utilizzano Kafka Streams visitando TheirStack.com. La nostra piattaforma fornisce un database completo di aziende che utilizzano varie tecnologie e strumenti interni.
Fino ad ora, abbiamo dati su 1,476 aziende che utilizzano Kafka Streams.
Kafka Streams è utilizzato da una vasta gamma di organizzazioni in vari settori, inclusi "It Services And It Consulting", "It Services And It Consulting", "Financial Services", "It Services And It Consulting", "It Services And It Consulting", "Advertising Services", "Software Development", "Banking", "Information Services", "Hospitals And Health Care". Per un elenco completo di tutti i settori che utilizzano Kafka Streams, si prega di visitare TheirStack.com.
Alcune delle aziende che utilizzano Kafka Streams includono Purple Drive Technologies, Vectron Systems AG, Options Clearing Corporation, APPIC Solutions LLC, inserve GmbH, DoubleVerify, Dice, Standard Chartered, Experian, Optum e molte altre. Puoi trovare un elenco completo di 1,476 aziende che utilizzano Kafka Streams su TheirStack.com.
Secondo i nostri dati, Kafka Streams è più popolare in Stati Uniti (595 companies), Regno Unito (110 companies), India (70 companies), Spagna (66 companies), Germania (46 companies), Francia (36 companies), Canada (29 companies), Paesi Bassi (23 companies), Brasile (16 companies), Svizzera (13 companies). Tuttavia, è utilizzato da aziende in tutto il mondo.
Puoi trovare aziende che utilizzano Kafka Streams cercandolo su TheirStack.com. Tracciamo le offerte di lavoro di milioni di aziende e le utilizziamo per scoprire quali tecnologie e strumenti interni stanno utilizzando.
Kafka Streams è utilizzata in 48 paesi