Complex Event Processing Software
Best Complex Event Processing Software include:
TIBCO BusinessEvents, IBM Event Streams, Oracle Complex Event Processing, Sybase Event Stream Processor (Aleri), discontinued, Amazon Managed Streaming for Apache Kafka (Amazon MSK), Microsoft SQL Server StreamInsight, WebSphere Business Events, and Apache Pulsar.
The TIBCO Streaming (StreamBase®) platform is a high-performance system for rapidly building applications that analyze and act on real-time streaming data. Using TIBCO Streaming, users can rapidly build real-time systems and deploy them at a fraction of the cost and risk of other…
IBM Event Streams is a high-throughput, fault-tolerant, event streaming solution. Powered by Apache Kafka, it provides access to enterprise data through event streams, enabling businesses to unlock insights from historical data, and identify and take action on situations in real…
WSO2 Enterprise Integrator (WSO2 EI) is an open-source hybrid integration platform providing graphical and CLI tooling, integration runtimes, and monitoring with a variety of deployment options. The integration runtime engine is capable of playing multiple roles in an enterprise…
EVAM is a real-time Continuous Intelligence Platform for customer journey orchestration having real-time data integration and streaming advanced analytics with ML/AI.Evam Continuous Intelligence Platform is deployed in different industries including Telco, Banking, Retail & Loyalty,…
Luna Streaming, from DataStax headquartered in Santa Clara and now featuring technology and support from Kesque following the company's acquisition by DataStax in 2020, is a production-ready distribution of Apache Pulsar including 24/7 expert enterprise support.
Astra Streaming from DataStax, presently in beta, is multi-cloud Streaming-as-a-Service, built on Apache Pulsar. It is a cloud-native messaging and event streaming platform powered by Apache Pulsar. Astra Streaming allows users to build streaming applications on top of an elastically…
Microsoft SQL Server StreamInsight is the company's complex event processing (CEP) platform to help businesses create event-driven applications and derive better insights by correlating event streams from multiple sources, boasting near-zero latency. It can be freely downloaded.
Apama Streaming Analytics is a platform for streaming analytics and intelligent automated action on fast-moving big data. Combining event processing, messaging, in-memory data management and visualization, this platform is presented as a complete solution to turn relentless data…
AWS Data Pipeline is a web service used to process and move data between different AWS compute and storage services, as well as on-premises data sources, at specified intervals. With AWS Data Pipeline, users can regularly access data where it’s stored, transform and process it at…
What is Complex Event Processing Software?
Complex Event Processing (CEP) software tracks, processes, and analyzes raw data about things that happen (events), then draws possible cause-and-effect conclusions based on the relationship or timing between events. These techniques capture and analyze multiple streams of data to detect trends, events, patterns, opportunities, and threats as they happen, allowing for a quick and efficient response.
For example, a self-driving car may use CEP to determine that an object with a combination of red and white coloring, a hexagonal shape, and placement at intersections would be a stop sign, which then informs the driving systems to control deceleration and certain distance of the object. The CEP software would use this collection of data to help the AI distinguish a stop sign from a yield sign, which has a triangular shape, so it can make the best decision.
CEP software manages and analyzes a large volume of events happening at once. It is useful for stock market trading, health care, predictive maintenance, real-time marketing, AI management, predictive sales analysis, and fraud detection. This is because the essence of CEP is the ability to track, analyze, and store multiple data events to determine opportunities (e.g. developing marketing profile, future stock prices) or threats (e.g. security breaches, operating system issues). Data scientists who detect fraud or manage operational intelligence within these industries would find CEP software useful.
CEP overlaps with real-time interaction management software, operational analytics software, and streaming analytics software in that they all manage, analyze, and store information from data streams. Compared to these, CEP software boasts more robust analytic tools because of its ability to draw conclusions from multiple sources of information, allowing for quicker and more thorough reporting.
Complex Event Processing Software Features
These are the most common features across CEP software products:
- Activity monitoring
- End-to-end automation
- Event-pattern detection
- Single event processing
- Event abstraction
- Event filtering
- Event aggregation
- Event transformation
- Event hierarchy models
- Event prediction
- Detecting causal, membership, and timing relationships between events
- Abstracting event-driven processes
- Data analysis and reporting
- Data synthesis
- Data storage
- Opportunity and threat detecting, analysis, and reporting
Complex Event Processing Software Comparison
When choosing the best event management software for you, consider these factors:
Processing engine power: The number of data streams and the amount of data therein can take a toll on the processing power needed to run CEP software efficiently. If you anticipate working with a high number of data streams, the larger platforms like Amazon Kinesis and Google Cloud Dataflow use serverless architecture to help ensure smooth, effective, and uninterrupted processing.
Programming language support: One of the most important considerations in selecting CEP software is the programming language(s) they support so they can work with other software or integrations you may be using. For example, Apache Flink only supports Scala and Java, but Apache Spark supports Java, Scala, Python, and SQL.
Low latency support: Some CEP software struggles with low latency, meaning that data stream analysis and event prediction error risk increases if it is dependent on time-sensitive data. Apache Kafka, Apache Flink, and Google Cloud Dataflow are explicit in their support for very low latency.
Open-source or managed software: A large number of CEP software, such as WSO2 Analytics Platform and the Apache collection, are open-source, meaning that they are low-cost or free, and may accommodate more niche concerns such as message delivery semantics. However, this means that the user will most likely need to install, integrate, update, and troubleshoot the software manually, which will require more support from your IT staff. Some CEP vendors, such as Amazon Kinesis, Google Cloud Dataflow, and IBM Streams, manage the software for you. However, their functionality may be limited if you need more specific techniques, their cost can increase substantially if you are working with a large amount of data, and you will not be able to control server uptime.
CEP software has many free open-source solutions. For enterprises looking for a managed or serverless CEP solution, products can range from $200 to $1900 per month at their lowest cost, with additional costs stemming from the number of data streams processed per hour or per unit. Most paid products offer free trials and custom pricing plans.
The following articles may help you will make the best CEP decisions for your business: