使用Apache Storm的公司
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.
使用Apache Storm的公司列表
curl --request POST \
--url "https://api.theirstack.com/v1/companies/search" \
--header "Accept: application/json" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer <api_key>" \
-d "{
\"company_technology_slug_or\": [
\"apache-storm\"
]
}"Technology
is any of
Apache Storm
员工数633收入$7MDefense and Space ManufacturingApache Storm高置信度
员工数6.2k收入$1.5BIT Services and IT ConsultingApache Storm高置信度
员工数201Professional ServicesApache Storm高置信度
员工数1.5k收入$1.2BSoftware DevelopmentApache Storm高置信度
员工数1.2k收入$681MIT Services and IT ConsultingApache Storm高置信度
员工数32Chemical ManufacturingApache Storm高置信度
员工数51收入$3.1MIT Services and IT ConsultingApache Storm高置信度
员工数25IT Services and IT ConsultingApache Storm高置信度
员工数42收入$2MIT Services and IT ConsultingApache Storm高置信度
员工数244Public SafetyApache Storm高置信度
我们拥有关于989家公司和用户使用Apache Storm的数据。我们的Apache Storm用户和客户列表可供下载，并附有重要的公司信息，包括行业分类、组织规模、地理位置、融资轮次和收入数据等。
技术使用统计和市场份额
如何定位 Apache Storm 用户
- 如何自定义此列表？
您可以根据地理位置、行业、公司规模、收入、技术使用、职位发布等需求自定义此数据。您可以将数据下载为Excel或CSV格式。
- 如何在公司采用此技术时收到通知？
您可以为此数据设置提醒。您可以通过选择您感兴趣的技术开始，当有新公司使用该技术时，您将收到收件箱中的提醒。
- 如何将此数据导入我的CRM？
您可以将此数据导出为Excel文件，然后导入到您的CRM中。您也可以将数据导出到API。
常见问题
我们的数据来源于从数百万家公司收集的职位发布。我们监控公司网站、招聘网站和其他招聘平台上的这些发布。分析职位发布提供了一种可靠的方法来了解公司正在使用的技术，包括他们使用的内部工具。
我们每天刷新数据，以确保您访问的是最新的信息。这一频繁的更新过程保证了我们的洞察和情报反映行业的最新发展和趋势。
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.