A Comprehensive List of Big Data Technologies
Big data technologies have become increasingly important for businesses to manage and analyze large volumes of data. The technologies have evolved to become more complex, with a range of different tools and solutions available for different types of data analysis and processing. Here is a list of some of the big data technologies in demand today:
• Apache Hadoop: Hadoop is the most widely used big data platform, and it provides a distributed storage system and processing power to manage and analyze large amounts of data.
• Apache Spark: Spark is a distributed computing platform that is used to process and analyze large amounts of data. It is used for handling streaming data and is compatible with Hadoop.
• Apache Kafka: Kafka is a distributed streaming platform that is used to process and analyze streaming data in real-time.
• Apache Storm: Storm is a distributed real-time computation system that is used to process and analyze streaming data.
• Apache Cassandra: Cassandra is a distributed database system that is used to store and manage large amounts of data.
• Apache Solr: Solr is an open-source search platform that is used for indexing and searching large amounts of data.
• Apache Flink: Flink is a distributed stream processing engine that is used to process and analyze large amounts of streaming data.
• HBase: HBase is a distributed database system that is used to store and manage large amounts of data in a distributed environment.
• MongoDB: MongoDB is a document-oriented NoSQL database system that is used to store and manage large amounts of data.
• Elasticsearch: Elasticsearch is an open-source search and analytics engine that is used to store and search large volumes of data.
• Apache NiFi: NiFi is a data flow system that is used to manage and process large volumes of data.
• Redis: Redis is an in-memory data structure store that is used to store and manage large volumes of data.
• Presto: Presto is a distributed SQL query engine that is used to query and analyze large amounts of data.
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