comphead commented on issue #16622:
URL: https://github.com/apache/datafusion/issues/16622#issuecomment-5739668277

   For example, Apache Spark follows a SemVer-inspired versioning strategy, 
`x.y.z`, with some project-specific deviations:
   
   * **`x` — Major release:** roughly once a year. This is where breaking 
changes, API removals/deprecations, dependency upgrades, and other changes 
incompatible with the previous major line can happen. It is the point where 
significant migrations may be required.
   * **`y` — Feature release:** historically quarterly. These releases add new 
features, performance improvements, API additions, and bug fixes, while 
maintaining compatibility within the major line. Public APIs can be added, but 
existing public APIs are not changed or removed.
   * **`z` — Maintenance release:** released as needed for critical bug fixes 
and security/correctness fixes. These are intended to be patch-level, 
compatible updates.
   
   Spark's current release policy is evolving toward an annual major + 
quarterly feature-release cadence. The **last feature release of each major 
line is designated as LTS and receives 18 months of maintenance**. Spark 3.5.x 
is a special extended-LTS case, with that period ending in November 2027.
   
   That said, API stability also depends heavily on the project's maturity and 
evolution velocity. Spark is a mature project, whereas DataFusion is still 
evolving rapidly, so applying the same compatibility guarantees today may not 
be practical.
   
   But I agree that, eventually, DataFusion will probably reach a point where 
adopting a similar versioning and release strategy makes sense.
   


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