FlowerDocs 2025.3 : Performance Benchmarks

Uxopian Software
Engineering Team · Uxopian Software

At a glance : what the numbers say

FlowerDocs 2025.3 was tested under sustained load across six real-world document management scenarios. Here are the three numbers that matter most.

5,786 req/s
Document reads · 17ms avg latency
3,173 req/s
Metadata creation · 31ms avg latency
1,143 ms
Full-text search avg · 1M+ documents

These figures were measured with 100 concurrent users over a sustained 10-minute window per scenario, run across all six scenarios back-to-back on the same platform instance, making memory leak detection possible alongside throughput measurement.


Architecture and test configuration

The test infrastructure runs on a 4-core pod configuration with Redis caching and OpenSearch indexing. Object storage relies on an S3-compatible layer. The Gatling load testing framework generates the traffic, and every result is compared against the previous release to catch regressions before they ship.


What we tested : six production scenarios

Each scenario reproduces an everyday workflow of a document management platform.

S1 Create documents with randomized metadata
S2 Create documents with metadata + content (randomized size and MIME type)
S3 Get documents and their metadata
S4 Update document metadata
S5 Delete documents
S6 Search documents by metadata across 1M+ documents
Load conditions : 100 concurrent users, sustained continuously over a 10-minute test, repeated across 6 consecutive scenarios on the same platform, enabling memory leak detection over a full hour. All response times in milliseconds.

Results : raw benchmark data

Without back-end event-driven Operation Handlers
ScenarioTotal requestsRPSMin (ms)Max (ms)Mean (ms)Std Devp50p75p95p99
S11,844,6413,069113,757321631365063
S2 ⚠407,3926722631,74014763065962292,559
S3 †3,524,4965,86448431778101418
S4 †1,842,4763,066113,1143218334057127
S5 †187,072311122,0273202274816469431,183
S645,147752504,0311,3295371,2391,7022,3162,652

⚠ S2 : isolated max outlier (31,740ms) reflects a single object storage timeout event under peak concurrent upload pressure.


Analysis : what the data tells us

Without event-driven handlers

The results reveal a robust infrastructure, supported by the 4-core-pod configuration and Redis, which handles pure metadata operations with remarkable efficiency.

Document reading dominates with 5,786 req/s and 17ms average latency, confirming the cache is working perfectly. Metadata creation and updates maintain high stability at around 30ms for approximately 3,000 req/s.

Document creation with content (S2) reveals an identified infrastructure constraint : under simultaneous large-file ingestion, throughput reduces to 122 req/s and max response time reaches 148.9 seconds, pointing to S3 storage layer pressure. FlowerDocs continued to handle requests correctly throughout.

Search at 1,143ms average on 1M+ documents remains acceptable, with OpenSearch and S3 identified as the primary bottleneck for complex operations.


What this means for you

  • check Everyday operations are fast and reliable. Reading, creating metadata, and updating documents all respond under 50ms at the 95th percentile, across thousands of concurrent requests.
  • check The caching layer works exactly as intended. Redis delivers sub-20ms average read latency at nearly 6,000 req/s, a clear validation of the architecture choices made in this release cycle.
  • info Document creation with content : an identified infrastructure constraint. Under simultaneous large-file ingestion, response times are linked to S3 storage layer pressure, not to FlowerDocs itself.
  • autorenew Continuous testing prevents regressions. Every version is benchmarked against the previous one, so past optimizations are never silently broken by new code.
Written by
Uxopian Software
Engineering Team
@Uxopian Software

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