Distributed Database Design Decisions to Support High Performance Event Streaming

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In an article earlier this year, I talked about comparing distributed databases in general. All of those considerations remain salient for choosing a database right for your use case. Yet for today let’s focus in on a particular aspect of capability: whether a database is a strong fit for an event streaming architecture.

The transition from batch-oriented processing to event streaming architectures is at the heart of what’s fundamentally shifting in this next tech cycle. Kafka was initially released in 2011, around the same era as the early NoSQL databases. Pulsar was slightly later, being invented at Yahoo in 2013. Many database architectures long predate the event streaming revolution, and their fundamental design decisions may be an anti-pattern for use with event streaming.

Databases are [or should be] designed for specific kinds of data, specific kinds of workloads, and specific kinds of queries. How aligned or far away from your specific use case a database may be in its design & implementation from your desired utility of it determines the resistance of the system. So, sure you can use various databases for tasks they were never designed for — but should you?

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