Database Versioning — Managing Schema Changes Across API Versions
DodaTech
Updated 2026-06-28
1 min read
In this tutorial, you'll learn about Database Versioning. We cover key concepts, practical examples, and best practices to help you understand and apply this topic effectively.
Database versioning ensures schema changes do not break API consumers by managing migrations, backward compatibility, and multi-version schema support at the database level.
class SchemaVersion:
def __init__(self, name: str):
self.name = name
self.columns: Dict[str, str] = {}
self.views: Dict[str, str] = {}
def add_column(self, name: str, col_type: str):
self.columns[name] = col_type
def add_view(self, name: str, query: str):
self.views[name] = query
def generate_v1_view(self) -> str:
return f"CREATE VIEW {self.name}_v1 AS SELECT id, name, status FROM {self.name}"
def generate_v2_view(self) -> str:
return f"CREATE VIEW {self.name}_v2 AS SELECT id, name, state, email FROM {self.name}"
schema = SchemaVersion("users")
v1_view = schema.generate_v1_view()
v2_view = schema.generate_v2_view()
print(f"V1 view: {v1_view}")
print(f"V2 view: {v2_view}")
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SDK Versioning — Managing Client Library Versions Alongside API Versions
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Schema Evolution — Managing API Schema Changes Over Time
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