Apache Storm

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Apache Storm is a distributed, fault-tolerant, open-source computation system for processing large volumes of high-velocity data.

Top Competitors and Alternatives of Apache Storm

The top three of Apache Storm’s competitors in the Stream Processing category are Apache Spark with 66.55%, Apache Flink with 9.03%, Microsoft App-V with 5.99% market share.

    Top Competitors and Alternatives of Apache Storm

    The top three of Apache Storm’s competitors in the Stream Processing category are Apache Spark with 66.55%, Apache Flink with 9.03%, Microsoft App-V with 5.99% market share.

    Customers of Apache Storm

    Around the world in 2023, over 1456 companies have started using Apache Storm as Stream Processing tool.

    Customers Employee Range City Region Country Social Links
    Wayfair, Inc. 10,000+ Boston Massachusetts United States
    Equinix, Inc. 10,000+ Redwood City California United States
    Cerner Corporation 10,000+ Kansas City Missouri United States
    Spotify Technology SA 10,000+ Stockholm Stockholm Sweden
    GlobalLogic 10,000+ San Jose California United States
    Jio 10,000+ Mumbai Maharashtra India
    Wells Fargo & Company 10,000+ San Francisco California United States
    Hitachi Ltd 10,000+ Tokyo Tokyo Japan
    Caterpillar, Inc. 10,000+ Peoria Illinois United States
    American Express Company 10,000+ New York City New York United States

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    Apache Storm Customers by Industry

    The three top industries that use Apache Storm for Stream Processing are Big Data (114), Artificial Intelligence (86), Machine Learning (86).

    Apache Storm Customers by Employee Size

    The majority of Apache Storm’s customers for the stream-processing category fall in the company size of 10,000+ employees (334 companies), 20 - 49 employees (247 companies), 1,000 - 4,999 employees (225 companies).

    Apache Storm Customers by Geography

    The top three geographies of Apache Storm for stream-processing are the United States with 767(50.03%), India with 166(10.83%), United Kingdom with 71(4.63%) customers respectively.

    Employees of Apache Storm

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    FAQ

    Find answers to the most often asked questions by users.

    Who are the top Apache Storm competitors?

    Apache Storm’s Top competitors in the stream-processing category are Apache Spark, Apache Flink, Microsoft App-V. You can view a full list of Apache Storm competitors here. 6sense uses advanced data mining and AI algorithms to track customers and competitors of Apache Storm and 40,000 other technologies on the internet.You can also compare Apache Storm and its feature with top competitors here : Apache Storm vs Apache Spark Apache Storm vs Apache Flink Apache Storm vs Microsoft App-V .

    What is Apache Storm customer distribution based on company size?

    The majority of Apache Storm’s customers for the stream-processing category fall in the company size of 10,000+ employees (334 companies), 20 - 49 employees (247 companies), 1,000 - 4,999 employees (225 companies). You can view a distribution chart of Apache Storm customers by company size here.

    What is Apache Storm market share in the stream-processing?

    Apache Storm has market share of 6.82% in stream-processing market. Apache Storm competes with 15 competitor tools in stream-processing category. The top alternatives for Apache Storm stream-processing tool are Apache Spark with 66.55%, Apache Flink with 9.03%, Microsoft App-V with 5.99% market share.

    What are the top industries that use Apache Storm?

    Top industries that use Apache Storm for stream-processing are Big Data (114), Artificial Intelligence (86), Machine Learning (86).

    What are the top countries that use Apache Storm?

    Around the world in 2023, over 1456 companies have started using Apache Storm as stream-processing tool. Companies using Apache Storm for stream-processing are majorly from United States with 767 customers. 50.03% of Apache Storm customers are from the United States. Other top countries using Apache Storm are India and United Kingdom with 166(10.83%) and 71(4.63%) customers respectively.

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