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Apache Storm is a free and open source distributed realtime computation system. Storm makes it easy to reliably process unbounded streams of data, doing for realtime processing what Hadoop did for batch processing. Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more. Storm is fast: a benchmark clocked it at over a million tuples processed per second per node. It is scalable, fault-tolerant, guarantees your data will be processed, and is easy to set up and operate.
711
entreprises
Nous disposons de données sur 711 entreprises qui utilisent Apache Storm. Notre liste de clients Apache Storm 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 |
---|---|---|---|---|
General Motors | États-Unis | Motor Vehicle Manufacturing | 167K | $161B |
LiveRamp | États-Unis | Advertising Services | 1.5K | $529M |
![]() Wayfair | États-Unis | Retail | 14K | $12B |
![]() Lookout | États-Unis | Computer And Network Security | 830 | $60M |
opentext | Canada | It Services And It Consulting | 19K | $3.9B |
WELLS FARGO BANK | États-Unis | Financial Services | 212K | $74B |
![]() Box | États-Unis | Technology, Information And Internet | 3.5K | $840M |
Amazon Web Services, Inc. | États-Unis | It Services And It Consulting | 1.5M | $3M |
EY | Royaume-Uni | Professional Services | 357K | $45B |
Visa | États-Unis | It Services And It Consulting | 26K | $31B |
Denken Solutions Inc | États-Unis | Staffing And Recruiting | 501 | $25M |
Wells Fargo | États-Unis | Financial Services | 196K |
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Statistiques d'Utilisation Technologique et Part de Marché
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Apache Storm est utilisé dans 33 pays
Il y a 8 alternatives à Apache Storm
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.
Nous actualisons nos données quotidiennement pour vous garantir un accès à l'information la plus récente disponible. Ce processus de mise à jour fréquente assure que nos insights et notre intelligence reflètent les derniers développements et tendances au sein de l'industrie.
Apache Storm is a real-time computation system that makes it easy to process unbounded streams of data. It is a distributed, fault-tolerant, and scalable framework written predominantly in the Clojure programming language. Apache Storm allows for the processing of vast amounts of data with low latency, making it ideal for applications where real-time analytics and data processing are critical.
In the realm of Stream Processing, Apache Storm holds a significant position as a robust and efficient framework for handling streaming data. Stream Processing technologies focus on processing continuous streams of data in real-time, enabling organizations to derive insights and make decisions instantly based on the most up-to-date information available. Apache Storm, with its ability to handle high-speed data streams and ensure fault tolerance, is a key player in this category.
Apache Storm was founded in September 2011 by Nathan Marz and later open-sourced under the Apache Software Foundation in 2014. The motivation behind creating Apache Storm was to address the need for a distributed, real-time computation system that could handle the challenges of processing high-velocity data streams with low latency. Since its inception, Apache Storm has gained popularity for its near real-time processing capabilities and fault tolerance features.
In terms of current market share, Apache Storm continues to be widely used in industries requiring real-time data processing, such as financial services, telecommunications, and e-commerce. While it faces competition from other stream processing frameworks like Apache Flink and Spark Streaming, Apache Storm still maintains a strong presence in the market. With the increasing demand for real-time analytics and the growth of IoT devices generating continuous streams of data, Apache Storm is likely to see further adoption and potentially grow its market share in the future.
Apache Storm is a powerful tool widely utilized by companies for real-time stream processing needs. By leveraging this cutting-edge technology, businesses can effectively analyze and process vast amounts of data in real-time, enabling them to make timely and informed decisions.
Apache Storm excels in providing low-latency processing capabilities, ensuring that real-time data is processed swiftly and efficiently. Unlike batch processing systems that may introduce delays, Apache Storm enables companies to analyze data as it flows in, allowing for rapid decision-making based on up-to-the-minute insights.
One of the key advantages of Apache Storm is its scalability. Companies can effortlessly scale their processing capabilities to handle increasing data volumes without compromising performance. This flexibility ensures that organizations can adapt to dynamic data processing requirements and maintain optimal performance levels even during peak usage periods.
Apache Storm offers robust fault tolerance mechanisms that ensure data processing tasks are resilient to failures. In the event of node failures or system disruptions, Apache Storm's fault tolerance features enable seamless recovery and continuity of data processing operations. This reliability minimizes downtimes and data loss, enhancing the overall stability of the system.
By harnessing the power of Apache Storm, companies can achieve real-time data processing with minimal latency, enhanced scalability, and heightened fault tolerance capabilities, setting them apart from other technologies in the stream processing domain.
Apache Storm is a popular technology in the category of Stream Processing, utilized by various companies to handle real-time data processing needs. Here are a few real case studies showcasing how some companies effectively leverage Apache Storm:
1. Twitter: Twitter, a well-known social media platform, harnesses Apache Storm for real-time data analysis and processing. Twitter uses Apache Storm to power its real-time analytics, allowing for instant processing of the massive amount of data generated by user interactions, tweets, and trending topics. The platform started using Apache Storm several years ago to enhance its data processing capabilities and ensure timely insights for its users.
2. Airbnb: Airbnb, the renowned online marketplace for lodging and tourism experiences, relies on Apache Storm for stream processing tasks. Airbnb utilizes Apache Storm to manage and process streaming data related to user activity, bookings, and various operational metrics. By implementing Apache Storm, Airbnb ensures that data insights are generated in real-time, enabling the platform to make informed decisions promptly. The company integrated Apache Storm into its data infrastructure to handle the continuous stream of data effectively.
3. Spotify: Spotify, a leading music streaming service, employs Apache Storm for its real-time event processing requirements. Spotify utilizes Apache Storm to analyze and process user interactions, music playback data, and recommendation systems in real time. By leveraging Apache Storm, Spotify enhances its ability to provide personalized recommendations and improve user experience through dynamic data processing. The implementation of Apache Storm at Spotify has enabled the company to stay agile in responding to user behaviors and preferences on the platform.
These case studies exemplify how prominent companies like Twitter, Airbnb, and Spotify leverage Apache Storm for stream processing to drive real-time data analysis, enhance user experiences, and improve operational efficiencies. The adoption of Apache Storm by these companies underscores its significance in managing and processing streaming data effectively in today's data-driven landscape.
Vous pouvez accéder à une liste actualisée des entreprises utilisant Apache Storm 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 711 entreprises qui utilisent Apache Storm.
Apache Storm est utilisé par une large gamme d'organisations dans divers secteurs, y compris "Motor Vehicle Manufacturing", "Advertising Services", "Retail", "Computer And Network Security", "It Services And It Consulting", "Financial Services", "Technology, Information And Internet", "It Services And It Consulting", "Professional Services", "It Services And It Consulting". Pour une liste complète de tous les secteurs utilisant Apache Storm, veuillez visiter TheirStack.com.
Certaines des entreprises qui utilisent Apache Storm incluent General Motors, LiveRamp, Wayfair, Lookout, opentext, WELLS FARGO BANK, Box, Amazon Web Services, Inc., EY, Visa et bien d'autres encore. Vous pouvez trouver une liste complète des 711 entreprises qui utilisent Apache Storm sur TheirStack.com.
Selon nos données, Apache Storm est le plus populaire dans États-Unis (309 companies), Inde (50 companies), Royaume-Uni (40 companies), France (17 companies), Espagne (17 companies), Canada (16 companies), Allemagne (11 companies), Australie (10 companies), Pays-Bas (8 companies), Japon (5 companies). Toutefois, il est utilisé par des entreprises du monde entier.
Vous pouvez trouver des entreprises utilisant Apache Storm 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.