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VERA Features and Benefits List

The VERA engine’s advanced features enhance performance, optimize computing resource utilization, and elevate the user experience.

Feature NameDescriptionBenefits for Ververica Users
Compute / Storage SeparationSeparating compute and storage in VERA enables each to scale independently.Allows for efficient scaling of stateful applications, enhanced resiliency, and cost optimization, especially in cloud-native environments.
Tiered StorageVERA reduces job downtime and improves scalability by synchronously trimming redundant state data and downloading state asynchronously.Balances state recovery speed with resource efficiency, improving scalability, resilience, and fault tolerance.
Streaming Join OptimizationVERA separates keys from values, storing large values separately with references in the log-structured merge-tree (LSM tree).Reduces CPU and I/O overhead, enabling faster data access and improved efficiency for use cases like anomaly detection and recommendation systems.
Scheduling FunctionsSpeeds up job restarts after failures or updates.Minimizes downtime, reduces operational overhead, and ensures stable stream processing under heavy loads.
Dynamic Complex Event Processing (CEP)Allows event processing rules to be changed in real-time without service interruption.Enables seamless collaboration between BI and upstream teams, ensuring stable data feeds while supporting real-time changes.
Create Database as Database (CDAS) & Enhanced CatalogsMinimizes downtime and data loss across distributed systems while providing real-time metadata for state and query management.Enhances reliability, performance, and scalability for large-scale stream processing systems with real-time state management.
Built-in Flink Machine Learning (ML)VERA includes pre-installed machine learning APIs from the Apache Flink® library.Provides real-time ML capabilities for critical applications like fraud detection, recommendation systems, and predictive maintenance.
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