Guide to ESP vs. CEP

Encora | July 06, 2023

Society, governments, businesses, and individuals rely increasingly on data for critical processes and activities, and the amount of data worldwide is rapidly amassing. A study shows that in 2010, the amount of data created worldwide amounted to 2 zettabytes. In 2020, the overall amount of data created worldwide was forecast to reach roughly 64.2 zettabytes. By 2025, that number is expected to reach 181 zettabytes. For context, one zettabyte is equal to approximately 1 billion terabytes. 
Many technology practices exist to process data and glean insights through pattern, relationship, and correlation recognition. Two key processes are complex event processing and event stream processing. 

This guide explains complex event processing vs. stream processing, also called ESP vs. CEP. 

What is complex event processing?

Complex event processing (CEP) is a technology that tracks, collects, processes, and analyzes real-time data to gain insights as the events occur. CEP aims to identify opportunities, threats, or other meaningful events in large volumes of rapidly changing and highly-varied data so that action can be taken immediately. Examples of events include occurrences that generate data or a change in state, such as communications like emails, text messages, or phone calls; reports; or values such as time or temperature. A complex event is a broader event category that typically involves a correlation and analysis of multiple events through pattern detection, abstraction, filtering, detecting relationships, and other techniques. 

How is CEP different from event stream processing?

Event stream processing is a technology that processes, analyzes, and acts upon events from a data stream. Like CEP, ESP works in real-time and provides businesses with crucial insights for effective decision-making. However, CEP and ESP do not apply to the same circumstances. ESP encounters events in the order in which they occur or arrive. CEP encounters many different events that are taking place at the same time in disparate locations throughout an IT system or network. 

Pros and Cons of CEP

CEP presents some distinct advantages and disadvantages. Here are a few considerations to keep in mind: 


  • Real-Time Insights - CEP enables real-time insights into data clouds from different locations. 
  • Complexity - CEP detects complex relationships and patterns from various sources and data streams. 
  • Scalability - CEP systems quickly scale to process and analyze immense volumes of events and data streams. 


  • Complexity - The flip side to the pro of complexity is that, in some cases, it can be challenging for companies to design rules and algorithms and fulfill the robust requirements of the sophisticated system. 
  • Continual Evolution - CEP systems must evolve as business requirements, event patterns, and data sources change. Managing constant growth and development may be challenging for some companies unless they have the right experts involved. 

Pros and Cons of ESP

Like CEP, ESP is beneficial in many ways and presents potential challenges. Here are some pros and cons to consider: 


  • Real-time Insights - ESP enables real-time insights into linear data and events from singular locations. 
  • Power Efficiency - With ESP, the algorithms do not have to process many events simultaneously, reducing the processing power demands.
  • Expedient - With ESP, processing can be fast because events are computed as they arrive, the computations are passed along quickly, and the system moves on. 


  • Resource Demands - ESP requires significant power, capacity, and bandwidth to process high-volume data streams in real time. This can be a challenge for companies that are not prepared or do not have adequate resources. 
  • Scalability - It can be costly and resource-intensive to scale ESP to handle large data volumes and fulfill requirements for low latency. 

When to Use CEP vs. ESP

While CEP and ESP handle and analyze event data, they do so differently. Thus, CEP and ESP are each ideal for different applications and use cases. Here are contexts in which each approach is beneficial. 


  • Fraud Detection - CEP can help financial institutions detect patterns and anomalies in transaction data from many different locations, accounts, and channels. 
  • Supply Chain Management - CEP can provide manufacturers and logistics professionals with insight into potential supply chain disruptions, delays, or issues using real-time event data from various IoT devices and data sources. 


  • Predictive Maintenance - ESP helps companies schedule proactive maintenance by analyzing real-time sensor data from equipment and machines. 
  • Application Analysis - ESP can process and analyze application log data and illuminate potential errors, bottlenecks, or security issues. 

CEP and ESP with Encora

Companies can partner with Encora to leverage the power of ESP, CEP, and other cutting-edge technologies to drive growth and success. Encora is deeply expert in the various disciplines, tools, and technologies that power emerging economies. This is one of the primary reasons clients trust Encora to lead the complete Product Development Lifecycle toward data-driven excellence. Contact us to learn more about ESP, CEP, and our software engineering capabilities.

Insight Content


Share this Post

Featured Insights