Welcome to the Big Data Technologies guide! This section explores the core tools and frameworks driving modern data engineering and analytics. Whether you're diving into distributed systems or real-time processing, here's a structured overview to help you navigate the landscape.
🧱 Key Components of Big Data Ecosystem
Hadoop
A distributed storage and processing framework using HDFS and MapReduce.Apache Spark
Fast, in-memory data processing engine for batch and real-time analytics.Apache Flink
Stream processing framework with low-latency and high-throughput capabilities.NoSQL Databases
Scalable solutions like MongoDB, Cassandra, and DynamoDB for unstructured data.
🌐 Applications & Trends
Big data powers industries through:
- Data Analytics
- Machine Learning
- Cloud Computing
Leverage AWS, Google Cloud, or Azure for scalable big data solutions.
🚀 Get Started with Big Data
Explore our Big Data Tutorial to dive deeper into foundational concepts and hands-on projects.
For real-time processing insights, check out Real-Time Data Pipelines.
Images are generated for illustrative purposes. For technical details, refer to official documentation.