Azure Stream Analytics vs. Sybase Event Stream Processor (discontinued)

Data enrichment is effectively done in stream analytics also checking the values with different functionality like windowing and group by clause is effectively working.

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

• Routing of data from multiple inputs to multiple output
• You create your own user define function.
• Intermediate query is working very effectively.

Incentivized

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

Incentivized

• Code competency is not that much effective
• Ml models can't be integrated with stream analytics

Incentivized

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

Incentivized

Azure Stream Analytics is easy to implement and also to integrate compare to other services like iot analytics

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

• Very nice roi while using it.
• Multiple integration is the best functionality

Incentivized

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

Incentivized