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Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
37,042
companies
Technoloy Usage Stadistics and Market Share
You can customize this data to your needs by filtering for geography, industry, company size, revenue, technology usage, job postions and more. You can download the data in Excel or CSV format.
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Apache Spark is used in 119 countries
There are 23 alternatives to Apache Spark
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Apache Spark
Company | Country | Industry | Employees | Revenue | Technologies |
---|---|---|---|---|---|
United States | Software Development | 9.5K | $600M | Apache Spark | |
United Kingdom | It Services And It Consulting | 357K | $45B | Apache Spark | |
United States | Financial Services | 76K | $135M | Apache Spark | |
United States | Software Development | 201 | $12M | Apache Spark | |
United States | Retail | 10K | $50M | Apache Spark | |
United States | It Services And It Consulting | 28K | $31B | Apache Spark | |
Singapore | Software Development | 10K |
| Apache Spark | |
United States | Computer Hardware Manufacturing | 293K |
| Apache Spark | |
United States | Financial Services | 57K | $36B | Apache Spark | |
Business Consulting And Services | 445K | $59B | Apache Spark |
We have data on 37,042 companies that use Apache Spark. Our Apache Spark customers list is available for download and comes enriched with vital company specifics, including industry classification, organizational size, geographical location, funding rounds, and revenue figures, among others.
Frequently asked questions
Our data is sourced from job postings collected from millions of companies. We monitor these postings on company websites, job boards, and other recruitment platforms. Analyzing job postings provides a reliable method to understand the technologies companies are employing, including their use of internal tools.
We refresh our data daily to ensure you are accessing the most current information available. This frequent updating process guarantees that our insights and intelligence reflect the latest developments and trends within the industry.
Apache Spark is a powerful open-source unified analytics engine designed for big data processing and analytics. It provides a lightning-fast cluster computing framework for large-scale data processing tasks. Spark supports a variety of programming languages and offers high-level APIs in Java, Scala, Python, and R. One of the key features that sets Apache Spark apart is its in-memory computing capabilities, which enable data processing at lightning speeds by caching data in memory across multiple nodes in a cluster.
Apache Spark falls under the category of Big Data Tools, specifically within the realm of distributed data processing frameworks. It excels in handling complex data processing tasks across large datasets by leveraging in-memory computing and parallel processing. Spark's ability to seamlessly integrate with other big data technologies like Hadoop and support various data sources makes it a versatile tool for data engineers and data scientists working on big data analytics projects.
Founded in 2009 by researchers at the UC Berkeley AMPLab, Apache Spark was initially motivated by the limitations of the MapReduce framework in Hadoop for iterative and interactive processing. The creators sought to address the shortcomings of MapReduce by developing a faster and more efficient data processing engine, leading to the birth of Apache Spark. Since its inception, Apache Spark has gained significant traction in the big data industry and has become a preferred choice for organizations dealing with large-scale data processing and analytics tasks.
Apache Spark currently holds a substantial market share in the Big Data Tools category, with a growing trend expected in the future. As more businesses recognize the importance of real-time data processing and analytics, the demand for robust big data tools like Apache Spark is projected to increase. With its ability to handle diverse data processing workloads efficiently, Apache Spark is likely to see continued growth and adoption in the big data analytics landscape.
You can access an updated list of companies using Apache Spark by visiting TheirStack.com. Our platform provides a comprehensive database of companies utilizing various technologies and internal tools.
As of now, we have data on 37,042 companies that use Apache Spark.
Apache Spark is used by a diverse range of organizations across various industries, including "Software Development", "It Services And It Consulting", "Financial Services", "Software Development", "Retail", "It Services And It Consulting", "Software Development", "Computer Hardware Manufacturing", "Financial Services", "Business Consulting And Services". For a comprehensive list of all industries utilizing Apache Spark, please visit TheirStack.com.
Some of the companies that use Apache Spark include Databricks, EY, JPMorgan Chase Bank, N.A., Dice, Amazon.com, Visa, Agoda, Apple, Capital One, Deloitte and many more. You can find a complete list of 37,042 companies that use Apache Spark on TheirStack.com.
Based on our data, Apache Spark is most popular in United States (10,546 companies), United Kingdom (2,033 companies), India (1,007 companies), France (906 companies), Spain (709 companies), Germany (671 companies), Canada (667 companies), Brazil (449 companies), Netherlands (407 companies), Australia (376 companies). However, it is used by companies all over the world.
You can find companies using Apache Spark by searching for it on TheirStack.com, We track job postings from millions of companies and use them to discover what technologies and internal tools they are using.