Amazon Managed Streaming for Apache Kafka (Amazon MSK) vs. IBM Event Automation vs. Spotfire Streaming

IBM Event Streams is well suited for companies developing event driven Microservices. One of the biggest challenger with microservices is that your data gets distributed into little silos - event streaming (or better known as event sourcing) allows you to get a central source of truth in your event store. We are taking this approach with IBM Event Streams and it is well suited for building an event streaming / sourcing architecture.

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Taking data from various sources including files, databases, web services, applying some complex rules, transforming, aggregating and producing a result. This is what Spotfire Streaming does best.
- If one needs connectivity to special services as secured databases or web services, building interactive web apps, those are probably tasks that shall be addressed with different tools.

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• It is adaptive and helps us create more engaging experiences on our platforms.
• The Key metrics dashboard is rich with insights.

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• Processing events in real-time with real low latency and high throughput.
• 100% visual program language, which can be extended by common languages like Java, Python and .NET.
• Reduced time to prototype, create an application and deployment, which reduces the software lifecycle.
• Real robust engine and server. Barely heard of customers having issues in production.

• Provide Capabilities to connect the Event Streams via REST Proxy.
• Schema Registry to handle Avro Formats.
• Provide Kafka Connect Sink & Source Connectors.

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• Being a niche tool, there's not much community support
• It is on prem, making it slow to boot. not cloud native (It could be that it is our org's issue)
• The dev environment is very tough to understand for large projects due to the wire style UI/UX

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The product was very user friendly and extremely easy to get started with. The documentation is excellent and the free tier makes it very easy to get started with without having to make deep or long term financial commitments.

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The usability is good in terms that it gets well integrated with the Spotfire suite but the only few issues I have is the tough UI/UX (learning curve, if the project is huge) and unable to find many users and devs to help with the queries. At the end it is solely based on the documentation provided which is never enough

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I met with the support team and they have deep technical and development understanding of the needs and the problems which IBM Event Streams addresses. If you are looking for a product backed by a highly technical support team then IBM Event Streams is probably the best choice. I was specifically impressed by the level of technical understanding my support team demonstrated.

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Spotfire Streaming support is prompt and to the point. They help with best practices and learning from existing projects.

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In Event Streams, applications send data by creating a message and sending it to a topic. To receive messages, applications subscribe to a topic. High availability and reliability. Event Streams offers a highly available and reliable Apache Kafka service running on IBM Cloud. Event Streams. Event Streams stores three replicas of your data to ensure the highest level of resilience across three availability zones.

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We are using Dataflow (by Google).The development time in Spotfire Streaming is definitely shorter because its GUI based. Dataflow handles late arrivals after the window closes, not sure Spotfire Streaming can do that. Dataflow can run GCP as a managed service which is why we chose that tool for our new product.

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• In using downstreams, the minimal features and the rate of releases were slow, makes us feel that there's no upgrades and other than that there's poor marketing of the product.
• The adoption around the service is low, requires focused marketing.
• Lack of visibility into topic depth , Monitoring capabilities

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• While we haven't specifically integrated Spotfire Streaming into our product development, it has allowed us to see the benefits of real-time streaming data.
• We have much more visibility into how our longer term roadmap will look and what we should focus on.

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