Apache Flink vs. Tealium Customer Data Hub

In well-suited scenarios, I would recommend using Apache Flink when you need to perform real-time analytics on streaming data, such as monitoring user activities, analyzing IoT device data, or processing financial transactions in real-time. It is also a good choice in scenarios where fault tolerance and consistency are crucial. I would not recommend it for simple batch processing pipelines or for teams that aren't experienced, as it might be overkill, and the steep learning curve may not justify the investment.

Incentivized

For more suited, I'll say highly regulated industry around data like healthcare, insurance, finance, where Tealium can be very helpful and for clients that don't have much different channels where they interact with their clients. So companies that only sell on internet and are a small company, I can see Tealium being the best usage for these clients, for these companies.

Incentivized

• Low latency Stream Processing, enabling real-time analytics
• Scalability, due its great parallel capabilities
• Stateful Processing, providing several built-in fault tolerance systems
• Flexibility, supporting both batch and stream processing

Incentivized

• Simple tag management that is tough to beat. So many solutions that are incredibly simple to setup and gather data for.
• Security around the data is key and Tealium excels in this area.
• The speed impact of the tag setup is key to optimizing and allowing our web properties to run more effectively, which is a better experience for the end user.

Incentivized

• Python/SQL API, since both are relatively new, still misses a few features in comparison with the Java/Scala option
• Steep Learning Curve, it's documentation could be improved to something more user-friendly, and it could also discuss more theoretical concepts than just coding
• Community smaller than other frameworks

Incentivized

• Audiences—don't they technically exist in Tealium? They are just streamed—no count, no backfill, etc.
• Working backward to identify issues involves lots of clicking in the UI, going from audience to audience attribute, badge to event attribute, and so on.
• You have to wait for a Real-Time event to see the payload. There is no sample or other option.

Incentivized

I already know that my company has no plans to discontinue use of Tealium. We are heavily reliant on it due to a huge number of product teams and developers we would have to work with to place tags across many pages. Tealium is already there on the pages, and our application/product teams are familiar with how to integrate it. It is just the simplest way to ensure that new data requirements are implemented in a timely manner.

Incentivized

Tealium iQ Tag Management System does exactly what it is intended for, it manages vendortags. Changes can be made to websites and apps in minutes. The frontend is well structured, updates are easy to carry out, and Tealium support is available at all times.

Incentivized

It's been flawless as far as I am concerned.

Incentivized

Sometimes publishing can take longer than expected

Incentivized

The support team often is so quick to respond and so helpful when it comes to working with the needs of my clients and being able to resolve potential shortcomings or technical issues or surrounding the tool. There have been times more recently that I’ve gotten more generic service rather than the tailored experience that I have come to expect.

Incentivized

Did what we needed to onboard us onto the platform

Incentivized

Implementation had some bumps in the road and it was new for all of us, but for the most part, it was easier than many other implementations we've done with other technologies.

Incentivized

Apache Spark is more user-friendly and features higher-level APIs. However, it was initially built for batch processing and only more recently gained streaming capabilities. In contrast, Apache Flink processes streaming data natively. Therefore, in terms of low latency and fault tolerance, Apache Flink takes the lead. However, Spark has a larger community and a decidedly lower learning curve.

Incentivized

Tealium Customer Data Hub can do it all in one. Whereas, I think by using multiple Tealium Customer Data Hubs, we can utilize what each tool is really good at. In an ideal world, we'd like to use Tealium Customer Data Hub for everything, but one thing that we struggle with is Audience Segmentation, and we are looking for a one touch solution, without a lot of the work since the data is already there.

Incentivized

Like anything it could be cheaper but we still feel we get value from it.

Incentivized

Never had an issue, scales as we use it.

Incentivized

Very easy to work with and relatively cost effective

Incentivized

• Allowed for real-time data recovery, adding significant value to the busines
• Enabled us to create new internal tools that we couldn't find in the market, becoming a strategic asset for the business
• Enhanced the overall technical capability of the team

Incentivized

• There has been a near immeasurable return on customer data and improvement of our quality for our physical products due to be in tune with the customer. This has changed our way of doing things for the better to gain a better flow and overall workplace experience.
• A negative is that Tealium AudienceStream becomes harder to manuever and use data analytics for when a database has been existing for a fairly large amount of time. It goes from an agile ship to a huge vessel that takes many components to be able to move.

Incentivized