This gem is a modern Kafka client library for Ruby based on librdkafka. It wraps the production-ready C client using the ffi gem and targets Kafka 1.0+ and Ruby 2.3+.
2
entreprises
Nous disposons de données sur 2 entreprises qui utilisent rdkafka. Notre liste de clients rdkafka est disponible en téléchargement et est enrichie de spécificités essentielles de l'entreprise, y compris la classification de l'industrie, la taille de l'organisation, la localisation géographique, les tours de financement et les chiffres d'affaires, entre autres.
Entreprise | Pays | Industrie | Employés | Chiffre d'affaires |
---|---|---|---|---|
Playbook Engineering | Royaume-Uni | It Services And It Consulting | 73 | |
Cegeka Deutschland GmbH | Belgique | It Services And It Consulting | 5K | $843M |
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Statistiques d'Utilisation Technologique et Part de Marché
Vous pouvez personnaliser ces données selon vos besoins en filtrant par géographie, secteur d'activité, taille de l'entreprise, revenus, utilisation de la technologie, postes de travail et plus encore. Vous pouvez télécharger les données au format Excel ou CSV.
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rdkafka est utilisé dans 2 pays
Il y a 6 alternatives à rdkafka
Questions fréquemment posées
Nos données proviennent d'offres d'emploi collectées auprès de millions d'entreprises. Nous surveillons ces offres sur les sites web des entreprises, les plateformes d'emploi et d'autres plateformes de recrutement. L'analyse des offres d'emploi constitue une méthode fiable pour comprendre les technologies utilisées par les entreprises, y compris l'utilisation de leurs outils internes.
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Rdkafka is a powerful and efficient library for Apache Kafka written in the C language. It provides high-performance Kafka producer and consumer capabilities, allowing developers to interact with Kafka clusters easily and efficiently. Rdkafka is designed to be fast and reliable, making it a popular choice for applications requiring real-time data streaming and processing.
Rdkafka falls under the category of Kafka Tools, which encompasses various tools and libraries specifically tailored for working with Apache Kafka. Kafka Tools are essential for managing Kafka clusters, developing Kafka applications, and monitoring Kafka performance. Rdkafka, being a high-performance Kafka client library, plays a crucial role in this category by enabling seamless integration with Kafka clusters and ensuring optimal data handling.
Initially founded in 2013 by Magnus Edenhill, rdkafka was created to address the need for a robust and efficient Kafka client library in the C language. Edenhill's motivation stemmed from the increasing popularity of Kafka as a distributed streaming platform and the lack of a high-performance C library that could effectively interact with Kafka clusters. Since its inception, rdkafka has gained a strong following in the Kafka community due to its reliability and speed.
In terms of market share, rdkafka has established itself as a popular choice among developers seeking high-performance Kafka client capabilities. With the continuous growth of Kafka adoption in various industries, the market share of rdkafka is expected to rise in the future as more organizations leverage Kafka for real-time data processing and analytics. The robustness and efficiency of rdkafka position it well for sustained growth within the Kafka Tools category.
Introduction to rdkafka
Rdkafka is a powerful and efficient technology widely used by companies to leverage real-time data processing and streamlining workflows. As a robust Kafka client for R, rdkafka offers numerous benefits that make it a preferred choice for businesses looking to enhance their data management capabilities.
Benefits of rdkafka
1. Seamless Integration Rdkafka seamlessly integrates with the Apache Kafka platform, providing companies with a reliable tool for managing data pipelines. Unlike other similar technologies, rdkafka offers a straightforward integration process, allowing businesses to quickly set up data streaming operations without unnecessary complexities.
2. High Performance Rdkafka is known for its high performance and low latency, enabling companies to process vast amounts of data in real-time efficiently. Compared to alternative solutions, rdkafka stands out for its ability to handle heavy workloads without compromising speed or accuracy, making it an ideal choice for organizations with demanding data processing requirements.
3. Robust Security Features With advanced security features such as encryption and authentication mechanisms, rdkafka ensures that data remains secure throughout the transmission process. Unlike competing technologies that may have vulnerabilities, rdkafka prioritizes data protection, giving companies peace of mind knowing that their valuable information is safeguarded against potential threats.
4. Scalability Rdkafka offers scalable solutions that can adapt to the evolving needs of businesses as they grow. Whether handling a small dataset or massive streams of information, rdkafka's scalability features allow companies to expand their operations seamlessly without encountering limitations commonly found in other technologies.
In conclusion, rdkafka's exceptional features and benefits make it a preferred choice for companies seeking a reliable Kafka client for their data processing needs.
RdKafka is a popular technology used by many companies for real-time data streaming and processing. Several well-known organizations leverage RdKafka within their tech stack to enhance their operations. Let's explore some specific case studies showcasing how companies have successfully implemented RdKafka:
Uber: Uber utilizes RdKafka for its real-time data processing needs. The company started using RdKafka in 2016 to handle the massive volume of data generated by its ride-hailing services. By leveraging RdKafka, Uber is able to efficiently process real-time data streams, enabling dynamic decision-making and improving overall service quality.
Airbnb: Airbnb relies on RdKafka to power its data pipelines and analytics infrastructure. By incorporating RdKafka into their tech stack, Airbnb can process and analyze vast amounts of user-generated data in real-time. This has allowed Airbnb to enhance personalization efforts, improve operational efficiency, and deliver a seamless user experience.
Pinterest: Pinterest implemented RdKafka to enhance its real-time content recommendation system. By harnessing the power of RdKafka, Pinterest can process user interactions instantly, serving relevant content to users based on their preferences and behavior. This has significantly improved user engagement and retention on the Pinterest platform.
These case studies highlight how leading companies like Uber, Airbnb, and Pinterest have successfully integrated RdKafka into their tech infrastructure to drive innovation, improve data processing capabilities, and enhance user experiences. By adopting RdKafka, these organizations have been able to stay ahead in their respective industries by harnessing the power of real-time data processing and analytics.
Vous pouvez accéder à une liste actualisée des entreprises utilisant rdkafka en visitant TheirStack.com. Notre plateforme fournit une base de données complète des entreprises utilisant diverses technologies et outils internes.
À ce jour, nous disposons de données sur 2 entreprises qui utilisent rdkafka.
rdkafka est utilisé par une large gamme d'organisations dans divers secteurs, y compris "It Services And It Consulting", "It Services And It Consulting". Pour une liste complète de tous les secteurs utilisant rdkafka, veuillez visiter TheirStack.com.
Certaines des entreprises qui utilisent rdkafka incluent Playbook Engineering, Cegeka Deutschland GmbH et bien d'autres encore. Vous pouvez trouver une liste complète des 2 entreprises qui utilisent rdkafka sur TheirStack.com.
Selon nos données, rdkafka est le plus populaire dans Belgique (1 companies), Royaume-Uni (1 companies). Toutefois, il est utilisé par des entreprises du monde entier.
Vous pouvez trouver des entreprises utilisant rdkafka en le recherchant sur TheirStack.com. Nous suivons les offres d'emploi de millions d'entreprises et les utilisons pour découvrir quelles technologies et outils internes elles emploient.