Data Storage, Data Processing & Analytics Hadoop Etc
Introduction
Data is the new oil, and everyone wants it. The amount of data created by companies, governments and individuals continues to grow exponentially. Data storage, processing and analytics are critical for a company to stay competitive in the 21st century.
Big Data And Analytics
Hadoop is an open source framework for distributed storage and processing of large data sets on clusters of commodity hardware. Spark is another framework for big data processing, which is built on top of Hadoop.
Cassandra is a highly scalable multi-master database. MongoDB is an open source NoSQL database that uses JSON documents to store data in schemaless tables, which allows dynamic schema evolution as new fields get added to the document or existing ones change their type over time.
Data Storage And Processing
Hadoop
Hadoop is a framework for storing and processing large amounts of data. It’s used by many companies, including Facebook and Yahoo! It’s also open source so you can download it for free if you have the resources to set it up yourself. The main components of Hadoop are:
- HDFS (for storing data)
- MapReduce (for processing)
Hadoop, Spark, Cassandra And MongoDB
Hadoop is a framework for distributed storage and processing of large data sets on computer clusters. Spark is a fast and general engine for large-scale data processing. Cassandra is a highly available, scalable and flexible distributed database
Conclusion
We hope you enjoyed this look at some of the most popular data storage and processing tools. If you have any questions about these technologies or want to learn more about how they can help your company, please contact us today!
