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ِAvro, https://www.confluent.io/blog/avro-kafka-data/ - Coggle Diagram
ِAvro
The need for schemas
Robustness
Clarity and semantics
the doc string in each schema
helps producers know the type of the schema
very useful for multiple producers
Compatibility
what happens when the format changes
add or remove or alter fields
Example
fax number changed to mail
Schemas are Conversation
between producers and consumers
there has to be a defined way of communication between them
Eliminate the manual labor of data science
Effective Avro
Use enumerated values
require documentation for all fields
avoid non-trivial union types
reasonable schema and field naming
What is Avro
Open-source
data serialization format
using schema
Schema Registry
Avro needs the schema to be stored with the data when writing and reading
storing the schema with each record will maximize the size of the messages
schema registry
is where all the schema stored
https://www.confluent.io/blog/avro-kafka-data/