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

Like the name says, it is good for streaming data and analyzing. It is great to look at tuples at a fast rate, filtering, calling other sources to enrich data, can call APIs, etc. Could do better for ingest use cases, can do better with guaranteed delivery, etc.

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

• IBM Streams is well suited for providing wire-speed real-time end-to-end processing with sub-millisecond latency.
• Streams is amazingly computationally efficient. In other words, you can typically do much more processing with a given amount of hardware than other technologies. In a recent linear-road benchmark Streams based application was able to provide greater capability than the Hadoop-based implementation using 10x less hardware. So even when latency isn't critical, using Streams might still make sense for reducing operational cost.
• Streams comes out of the box with a large and comprehensive set of tested and optimized toolkits. Leveraging these toolkits not only reduces the development time and cost but also helps reduce project risk by eliminating the need for custom code which likely has not seen as much time in test or production.
• In addition to the out of the box toolkits, there is an active developer community contributing additional specialized packages.

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

There are well explained tutorials to get the user started. If you are looking for business application ideas, the user community offers a diversity of applications. It is very easy to launch applications on the cloud and can integrate with other analytic tools available on Watson Studio. It takes away the burden of the technology so that users can focus on business innovations.

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