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VERA's Underlying Technology

VERA (Ververica Runtime Assembly) enables you to connect, process, analyze, and govern your data in a single solution. It is the ultra-high performance, cloud-native engine that optimizes Apache Flink and powers Ververica’s Streaming Data Platform. VERA solves the challenges that come with managing large volumes of distributed data, by allowing you to quickly make mission-critical, data-driven decisions.

Rather than having to wait for data to be collected and processed before you can act on it, you can analyze and use data in real time. You can achieve an immediate realization of value, making your decisions with the most up-to-date information possible.

VERA Pillars

VERA's Core Pillars​

VERA functions at the core of Ververica Unified Streaming Data Platform. As you can see in the image, three technologies makeup the core pillars of VERA and form the foundation of its capabilities:

  • Streaming Data Movement
  • Real-Time Stream Processing
  • Streamhouse

When combined, VERA and these pillars provide a one-stop solution for all your data streaming needs, whether you are processing, storing, or moving data.

Streaming Data Movement​

Because all data lives in different places, your business decisions are also spread out over your architecture. Data lives in postgres. It lives in a MYSQL. It lives in any number of other operational data sources, and this has a huge effect on your tactical decisions.

Streaming Data Movement involves using Flink Change Data Capture as the end-to-end process that moves streaming data and events through VERA in three key steps.

  1. Loading the data generated from various applications and systems (often in different formats and volumes) and transforming it into a uniform type.
  2. Processing the transformed data in real time and making it actionable as it flows through the system.
  3. Delivering the processed data to destination systems for potential future use, all while maintaining data lineage and ensuring security.

This process provides several advantages, enabling you to:

  • Easily access, format, process and store any data
  • Use data for future decision making
  • Move your data and events into a common stateful processing layer
  • Access a unified, 365-degree, real-time view and processing window into your data
  • Develop applications with out-of-the-box support for Java, Python, or SQL

VERA transforms data into a uniform data set, regardless of where it orginated, and makes the data easily accessible and actionable so that you can use it to act quickly and make well-informed business decisions.

Real-Time Stream Processing​

Processing and acting on your data in real time allows you to extract immediate meaning and insight from data, and removes the historical lag and wait time of batch processing. Any piece of data that is inherently time-bound, whether happening asynchronously, or subject to an absolute time window guarantee, requires highly scalable, elastic, and stable real-time processing.

Because VERA decouples the storage and compute layers of the architecture, it can deliver both stream processing and batch processing for stateful computations over data streams. VERA manages the execution of Flink applications and seamlessly integrates with Flink and its APIs. This allows developers to process and analyze large amounts of data efficiently and extract insights in real time.

With unified batch and stream processing in one solution, you can:

  • Stop waiting for data to catch up, and instead make fast, reliable decisions using the freshest information available.
  • Take action on your data as it arrives, in whatever format it arrives, and use it to make immediate decisions.

With VERA, you can take action on your data as it arrives, in whatever format it arrives, and use it to make immediate decisions.

Streamhouse​

Streamhouse combines Apache Flink for stream processing with Apache Paimon on the streaming storage layer to deliver stream processing capabilities while maintaining near-real-time results on the Data Lake.

By providing a storage solution the combines the best of both real-time streaming and traditional Lakehouse batch processing, Streamhouse ensures you can:

  • Leverage nearly unlimited storage inside your streaming compute engine.
  • Query petabytes (or even exabytes) of data without compromising on cost-effective storage.
  • Perform both real-time and near real-time stream processing from a single engine, enabling informed decision-making with both current and historical data.

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