Apache Avro

data serialization, row-based, schema evolution, file format, storage
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Back in the dark ages of data – roughly 2009 – when Hadoop was king and serialization felt like an arcane art, Apache Avro emerged. The promise? A data serialization system that didn’t require pre-defined schemas at runtime, offering both compact data storage and rapid deserialization. Quite clever, really, though one does wonder if everyone fully grasped the schema evolution implications.

In practice, Avro is a bit like the meticulously organized librarian of the data world. It demands schemas – you just define them upfront. This rigidity is both its strength and weakness. While JSON and protocol buffers offer alternatives, Avro's schema evolution capabilities truly shine when data structures inevitably change. Today, it’s a cornerstone of many data pipelines, particularly within the Hadoop ecosystem and increasingly in streaming applications, quietly powering things behind the scenes for those who appreciate a bit of structure in the chaos.

Used together with Avro

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Jobs in using Apache Avro for but please no

data engineer

IT Engineer (Solution Architect) @ abn-amro

NL | 2025-12-22
This role is a misaligned opportunity for a data engineer with a focus on Kafka and Azure. The job description is vague, lacks specific technical requirements, and fails to define responsibilities... read more »
Data Streaming, BI, Kafka, Azure, Cloud Computing, Java, Linux, DevOps, Agile/Scrum, Management, Avro