Over the past six months, we have worked extensively with Microsoft Support to evaluate the Date Compression feature in Business Central, particularly for large G/L Entry Tables. Despite multiple configuration attempts and support, the feature has proven ineffective for high-volume datasets.

Test Scenario & Runtime Observations

We tested the feature in a real-world environments with ~ 50 Mio entries in the General Ledger Entry table. The goal was to reduce database size in preparation for a SaaS migration. The maximum throughput achieved was ~20,000 entries per hour, which translates to 10-20 hour runtime for a weeks data.

Our test efforts included: Creating and adjusting SQL indexes on relevant field, Modifying compression parameters (e.g. date ranges, dimension filters), Running compression jobs during off-peak hours to avoid contention, uninstalling everything but Microsoft Base Apps, Running tests on different environments and hardware sizings

None of these actions helped, so we concluded the feature impractical for production use in large enterprise environments.

The product team confirmed that there are no plans to improve the compression logic and that no internal benchmarks exist for large datasets.

Why This Matters:

• Efficient compression is critical for reducing database size and enabling smoother cloud migration.
• A scalable and well-documented compression process would benefit many partners and customers working with legacy data.
• Knowing the limitations of this feature upfront would have allowed us to advise our customers more accurately and avoid investing time in a non-viable solution.

Suggested Improvements:

• Optimize the compression logic to handle large datasets more efficiently.
• Introduce performance benchmarks and scalability guidelines for the Date Compression feature.
• Provide clear documentation on limitations and best practices for using this feature in real-world scenarios.

We believe enhancing this feature would significantly improve Business Central’s usability and cloud migration readiness for enterprise environments.