Aerospike vs. Sybase Event Stream Processor (discontinued)

We were developing an advertisement time auction application, where we had to store the client's personal details, advertisement-related details, location, and many other details. Moreover, we required a promotion, cookies, and a few more details from the front end. All this information is heavy in terms of size and cannot be lost if the server crash. So, we required an extremely fast disk database with high scalability and low throughput.

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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.

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• Low latency
• Stable
• Highly configurable
• increasing features

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

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• Load balancing per network segments.
• Reduction in price.
• Cross datacenter replication usage isn't so straightforward. Sometimes cross dc replication can have issues of bad data..

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

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If money isn't an issue, and you're not on the cloud, then I'd go with Aerospike. If you're the cloud ie, aws or azure, then i'd stick with dynamoDB or Cosmos then. Aerospike is definitely not something you want to put into the cloud. It doesn't work well w/ cross regions. If cross DC, you'll have to write some stuff for data integrity checks.

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Could be easier to use and install. Also developer experience needs some work

We used the community edition.

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Aerospike is much more performant than MongoDB, however there is much greater community adoption and support for mongo

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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.

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• Being able to power the same workload on a fraction of the servers has led to better ROI for my application.
• Less servers needed also meant less time to manage the cluster, leading to savings in engineering time

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

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A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info