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Big Data

Big data processing involves handling datasets that are too large or complex for traditional data processing tools, requiring distributed computing solutions.

Overview

Big data processing focuses on handling datasets that exceed the capacity of traditional database systems. Big data requires distributed computing and specialized tools.

Big data technologies enable processing of petabytes of data across clusters of computers, enabling analysis of massive datasets.

Key Technologies

Frameworks

Apache Spark
Hadoop
Flink
Storm
Kafka

Storage

HDFS
HBase
Cassandra
Data Lakes

Key Concepts

Distributed Computing

Process data across clusters of computers to handle large-scale datasets.

Data Lakes

Store vast amounts of raw data in data lakes for flexible analysis and processing.

Stream Processing

Process data streams in real-time as data arrives rather than in batches.

Scalability

Design systems that can scale horizontally to handle growing data volumes.

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