Proposal: Add DDSketch (Relative-Error Quantile Sketch)

## Proposal: Add DDSketch (Relative-Error Quantile Sketch)

**Summary:**
This issue proposes adding an implementation of [DDSketch](https://www.vldb.org/pvldb/vol12/p2195-masson.pdf), a mergeable quantile sketch with relative-error guarantees, to the `datasketches-cpp` library.

Benefits:
- Relative-error guarantees
- Mergeability for distributed processing
- Predictable memory usage
- Used in production (Datadog, OpenTelemetry)

## References

- VLDB 2019: [DDSketch Paper](https://www.vldb.org/pvldb/vol12/p2195-masson.pdf)
- [Datadog's sketches-java repo](https://github.com/DataDog/sketches-java)

## Proposed Design

- New class under `ddsketch.hpp`
- Logarithmic mapping of input values to buckets using configurable relative accuracy
- Compact, bounded memory footprint with optional bucket collapsing
- Mergeable histogram-style structure
- Serialization and deserialization support
- Unit tests and benchmarks included

## Compatibility

- No changes to existing APIs
- Implementation will be self-contained
- Optional: initial release could be marked experimental

## Next Steps

If there is community interest, I’m happy to:
1. Share a detailed design document
2. Begin work on the implementation and submit a PR
3. Iterate based on feedback

Would the maintainers be open to including DDSketch? Are there specific design or compatibility considerations I should address before proceeding?

Start by reading the DDSketch paper and Datadog's sketches-java reference. The proposed implementation belongs in ddsketch.hpp and should include serialization, deserialization, unit tests, and benchmarks. Done means a self-contained, mergeable DDSketch with configurable relative accuracy and bounded memory, without changing existing APIs.

Written by the indexing model from the issue text.