The purpose and benefits of data stream processing What is a Streaming Database?

Von Mia Liang * |

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Conventional database systems and data stream systems differ fundamentally from each other. Each solution has its own special use case. This article looks at what streaming databases do differently, better and sometimes worse.

Streaming databases show their strengths wherever information is transmitted and required in real time.
Streaming databases show their strengths wherever information is transmitted and required in real time.
(© Nmedia -

This article is the original version contributed by Girls Write Tech. Please find the German translation here: Wo spielen Streaming-Datenbanken ihre Stärken aus?

With a Relational Database Management System, otherwise known as an RDBMS, an administrator loads data at a predetermined frequency depending on their requirements. With a streaming database, on the other hand, data is collected, processed, and enriched in real-time - usually right after the data itself is created.

No intro to streaming databases would be complete without a mention of the fact that we are NOT talking about a particular database management system. Streaming databases can be any database that is configured to process streaming data in real-time. This can include time-series databases, in-memory data grids, and more.

Streaming databases are for any developer that needs to be able to respond to changes in real-time. They're particularly helpful in situations where you need to deploy real-time machine learning interfaces, which themselves depend on being able to process data almost instantly after a database is created.

Streaming Database Use Cases

One of the most important things to understand about how to use streaming data is that there is a wide range of different use cases for you to choose from depending on your needs. One of the most prominent of these involves the ways in which streaming data can be used to get data visualizations in real-time in a way that makes it easier to make better and more informed decisions moving forward.

Streaming data is a perfect opportunity to analyze the sheer volume of information that a business is creating on a daily basis in a far more effective way than humans could on their own. By being able to visualize this information in a way that makes it easy for absolutely anyone to understand, it lets organizations improve agility, increase the efficiency of their processes to eliminate waste, and more. It can even be a way to take existing consumer data to make more informed decisions regarding customer service improvements.

All of this insight lets organizational leaders take a far more proactive approach to their operations than would otherwise be possible. It lets them quickly identify opportunities so that they can capitalize on them, as opposed to missing out on them because they were unable to process data as fast as necessary.

Another important use case for streaming data has to do with how it enables you to set live alerts and notifications for important events across your enterprise. By setting up real-time alerts for those conditional adjustments that matter most to you, you can get notified that they've happened almost immediately. You no longer have to wait weeks or even months to learn that these changes occurred. Alerts are generated automatically so that the people who need this information to better do their jobs actually have it.

This is a terrific boost to small businesses in particular, as they're now able to respond to changes in consumer behavior or even in the market at large just as quickly as their larger competitors. Internally, it can also help prioritize maintenance on certain mission-critical pieces of equipment and other assets. If you have a complete, real-time picture of how a certain machine is operating, for example, you have everything you need to prioritize maintenance and get the most out of your budget.

Finally, streaming databases are a significant benefit when building applications that fall within the microservices architecture. With microservices, you're designing an application as a series of loosely coupled services that still work together to form a complete whole. This is in contrast to the monolithic applications of yesteryear.

Streaming databases are a great benefit in this use case because they allow for the free flow of necessary information from one service to another. Not only that, but information moves in real-time - thus allowing these services to still perform well individually, but to also work together in a way that dramatically improves the experience for end-users.

Pros and Cons of Streaming Databases

As stated, one of the biggest advantages of streaming databases is that they allow for both the speed and the flexibility needed for projects where teams need to be able to make more informed choices faster and more efficiently than ever. This is helpful in situations like fraud detection where every second counts.

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Streaming data is not ideal for projects that are working with very large data sets, however, or ones that depend on a deeper level of analysis. Streaming databases may also not be inherently compatible with the types of legacy systems that usually only support more traditional approaches to databases.

* Mia Liang works as a freelance writer for Girls Write Tech.