IBM Streams (discontinued) vs. Sybase Event Stream Processor (discontinued)

Streams is a good fit for situations requiring low end-to-end latency, have complex real-time analytical processing needs on large fast data, or where the reduction of operational costs is important. However, it is very much a data-in-motion technology and not well suited for situations such as some forms of machine learning where the entire historical data set needs to be operated on. Note that it's fairly common to use Streams to perform online scoring using models that were trained offline using other technologies.

Incentivized

These complex event processing platforms have the ability to process to multiple streams of data with low latency and ability to scale up well. It provides the ability to analyze streaming data real time and establish/investigate patterns with this streaming data and also deals with high-speed data very well.

Incentivized

• Query analysis of real time streaming data
• Filter out events based on time windows
• Scalability for large scale data, production tested

Incentivized

• Ability to capture data and investigate data for pattern fairly quickly
• Integrates well with Sybase database
• Ability to do data modeling

Incentivized

• Documentation could be more extensive, with more examples, although overall this is not too bad compared to some of the alternative solutions.
• Seems expensive to use in production.

Incentivized

• Configuring data streams could be made more intuitive to users
• Sometimes debugger tools are very slow

Incentivized

We are using Spark streaming as well as Storm for streaming options. Currently streams provides a better way of building applications easier faster and run efficiently. Also like the flexibility it provides with both us and SPL.

Incentivized

IBM WebSphere business elements which was more complex to set up and also more expensive especially in a large SAP environment, We were also looking to get ramped up with the product with minimal learning curve especially with good documentation available to get started with the product as well as the ability to deploy and maintain with relative ease on an ongoing basis.

Incentivized

• Ability to do more with less
• Admins and data analyst can now focus on more thinking tasks
• No negative impacts yet

Incentivized

• A positive impact on real-time analysis and patterns from streaming data
• Good speed
• Good documentation for setup
• No negative impact

Incentivized