The Realtime Data Processing compound pattern represents a solution environment where the Big Data platform is used to process streams of data in realtime or near-realtime, such as performing analytics on machine-generated or social media data.

Required (Core)

• Streaming Egress
• Realtime Access Storage
• High Velocity Realtime Processing
• Streaming Source
• Random Access Storage
• Automatic Data Replication and Reconstruction
• Automated Dataset Execution

Optional (Extension)

• Data Size Reduction
• Streaming Access Storage
• Complex Logic Decomposition
• Relational Sink
• File-based Sink

This pattern is covered in BDSCP Module 10: Fundamental Big Data Architecture.

For more information regarding the Big Data Science Certified Professional (BDSCP) curriculum,
visit www.arcitura.com/bdscp.