Make True Real-Time Data Processing A Reality

Use real-time decisioning to act quicker, react faster, mitigate risk, and generate more revenue.

TRUE REAL TIME DEFINED:

Ingest, Analyze, and ACT ON event data in under 10 milliseconds.

INTELLIGENT CONTEXTUAL DECISIONS
HIGH DATA
VOLUMES
ACCURATE AND CONSISTENT

Volt is the only platform that can analyze and make decisions on vast volumes of streaming data in true real time, without compromising on accuracy, resiliency, or consistency.

Business Overview

Six Use Cases of Real-Time Decisioning

Act On Data Immediately

Data is getting bigger, faster, and more varied. If you can’t act on your data immediately (i.e., in real time), you’ll lose your competitive edge. It’s no longer acceptable to store data first and process it later because you’ll be reacting to things (such as fraud) instead of proactively preventing them.

You need to process data first and store it later, which is exactly what Volt does and why the Volt Active Data Platform has become a must-have for any company seeking to fully capitalize on their real-time data.

The Challenges Of A Layered Architecture

Companies typically try to deal with processing and analyzing increasing data volumes and variety by adding layers to their stack. This approach has serious pitfalls:

  • It increases latency 
  • It increases the potential for inconsistency and errors
  • It makes failure-handling and compatibility checks difficult to orchestrate
  • It creates a bloated hardware footprint that increases TCO

As real-time data processing evolves to encompass in-the-moment contextual decisions, IT architectures need to become simpler, not more complex.

Report

Real-Time Data Processing: 5 Use Cases to Know

Volt Active Data’s Top-10 Capabilities

The Best Data Platform For Real-Time Data Processing

Real-time data processing has evolved from simple, fast data storage and retrieval to true real-time decisioning and actions. This means ingesting, storing, aggregating KPIs, detecting anomalies, and making decisions on your data in single-digit milliseconds.

A real-time data processing platform should be able to handle the entire ingest-through-act process for event-driven data in one stroke, through one layer, to support applications that can’t afford to lose data or compromise on latency and consistency at scale.

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