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Market Share
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Apache Spark
Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
- Big Data Infrastructure
Market Share of Apache Spark
- Current Customer The number of companies that currently use Apache Spark
- 8282
- Websites Added The number of companies that have started using Apache Spark in the past month.
NA- compared to last month
- Websites Dropped The number of companies that have stopped using Apache Spark in the past month.
NA- compared to last month
Top Competitors and Alternatives of Apache Spark
The top three of Apache Spark’s competitors in the Big Data Infrastructure category are Amazon Redshift with 35.94%Cloudera with 13.46%Amazon EMR with 12.93% market share.
Popular Comparisons
Top Competitors and Alternatives of Apache Spark
The top three of Apache Spark’s competitors in the Big Data Infrastructure category are Amazon Redshift with 35.94%Cloudera with 13.46%Amazon EMR with 12.93% market share.
Technology Stack Analysis
Compare Tech Stack of Apache Spark and Its Competitors
Get the list of top 5 common technologies used by Apache Spark and its competitors.
Customers of Apache Spark
Around the world in 2022, over 8066 companies have started using Apache Spark as Big Data Infrastructure tool.
Find which Apache Spark customers are ready to buy from you by using Slintel's buying intent score.
Apache Spark Customers by Industry
The three top industries that use Apache Spark for Big Data Infrastructure are Big Data (720)Machine Learning (637)Artificial Intelligence (522).
Apache Spark Customers by Employee Count
The majority of Apache Spark’s customers for the big-data-infrastructure category fall in the company size of 51-200 employees (1690 companies)11-50 employees (1439 companies)1k-5k employees (1142 companies).
Apache Spark Customers by Geography
The top three geographies of Apache Spark for big-data-infrastructure are the United States with 3589(44.53%)United Kingdom with 525(6.51%)India with 510(6.33%) customers respectively.
Employees of Apache Spark
Download Slintel’s Chrome Extension to get verified contact data of Apache Spark employees.
FAQ
Find answers to the most often asked questions by users.
Who are the top Apache Spark competitors?
Apache Spark’s Top competitors in the big-data-infrastructure category are Amazon RedshiftClouderaAmazon EMR. You can view a full list of Apache Spark competitors . Slintel uses advanced data mining and AI algorithms to track customers and of Apache Spark and 40,000 other technologies on the internet.You can also compare Apache Spark and its feature with top competitors here : Apache Spark vs Amazon Redshift Apache Spark vs Cloudera Apache Spark vs Amazon EMR .
What is Apache Spark customer distribution based on company size?
The majority of Apache Spark’s customers for the big-data-infrastructure category fall in the company size of 51-200 employees (1690 companies)11-50 employees (1439 companies)1k-5k employees (1142 companies). You can view a distribution chart of Apache Spark customers by company size .
What is Apache Spark market share in the big-data-infrastructure?
Apache Spark has market share of 24.41% in big-data-infrastructure market. Apache Spark competes with 11 competitor tools in big-data-infrastructure category. The top alternatives for Apache Spark big-data-infrastructure tool are Amazon Redshift with 35.94%Cloudera with 13.46%Amazon EMR with 12.93%market share.
What are the top industries that use Apache Spark?
Top industries that use Apache Spark for big-data-infrastructure are Big Data (720)Machine Learning (637)Artificial Intelligence (522).
What are the top countries that use Apache Spark?
Around the world in 2022, over 8066 companies have started using Apache Spark as big-data-infrastructure tool. Companies using Apache Spark for big-data-infrastructure are majorly from United States with 3589 customers. 44.53% of Apache Spark customers are from the United States. Other top countries using Apache Spark are United Kingdom India with 525(6.51%) 510(6.33%) customers respectively.
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