Comparing RPA bots vs native connectors for SAP data sync in integration-hub

BPM OutSystems
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1

We’re designing a new integration between OutSystems and SAP ERP for our procurement process. The integration-hub module offers two approaches: RPA bots that can automate SAP GUI interactions, or native SAP connectors using RFC/BAPI calls.

I’m trying to understand the trade-offs between these approaches, particularly around error recovery strategies, throughput benchmarks, and long-term maintenance requirements. Our volume is approximately 5,000 transactions per day with peaks up to 800/hour.

RPA bots seem more flexible since they can handle custom SAP screens and workflows that don’t have standard APIs. However, I’m concerned about reliability and what happens when SAP GUI layouts change during upgrades.

Native connectors appear more robust but require deeper SAP technical knowledge and may not support all our custom transactions. We have about 15 different SAP transaction codes we need to integrate.

What has been your experience with these approaches? Which performs better for high-volume scenarios, and how do maintenance costs compare over time?

2

Yes, hybrid is exactly what we ended up doing. We use the integration-hub module’s orchestration engine to route transactions based on type. Standard purchase orders, goods receipts, and invoice postings go through native RFC connectors. Custom approval workflows and special transaction types use RPA bots. The key is having a unified error handling framework that works across both methods. We built a custom monitoring dashboard that tracks success rates, throughput, and error patterns for both connector types in real-time.

3

From a maintenance perspective, native connectors have been far less problematic for us. We’ve had our SAP RFC integration running for 4 years with minimal changes - only when we add new fields or transaction types. Our RPA bots, on the other hand, broke three times during SAP upgrades when screen layouts changed. Each fix took 2-3 days of developer time. The total cost of ownership definitely favors native connectors if you’re planning a long-term solution.

4

Let me provide a comprehensive analysis of both approaches across the three key dimensions you mentioned.

Error Recovery Strategies:

Native Connectors:

  • Transactional integrity built-in through SAP’s RFC protocol
  • Automatic rollback on errors with clear error codes (RETURN table structure)
  • Easy to implement retry logic with idempotency checks
  • Can leverage SAP’s built-in error handling (BAPI_TRANSACTION_COMMIT/ROLLBACK)
  • Errors are structured and programmatically parseable

RPA Bots:

  • Error recovery requires screenshot analysis and screen scraping
  • Must implement custom checkpoint/restart logic
  • GUI-level errors (timeouts, connection drops) require sophisticated handling
  • Difficult to distinguish between business errors and technical failures
  • Recovery often requires human intervention for ambiguous states

Verdict: Native connectors provide superior error recovery with 95%+ automated recovery vs 70-80% for RPA bots.

Throughput Benchmarks:

Based on our implementations across 12 clients:

Native Connectors (RFC/BAPI):

  • Peak throughput: 180-250 transactions/minute
  • Average latency: 200-400ms per transaction
  • Scales linearly with connection pool size (up to SAP server limits)
  • Minimal memory footprint (2-5MB per connection)
  • Can handle your 800/hour peak easily with 5-10 concurrent connections

RPA Bots:

  • Peak throughput: 40-80 transactions/minute (highly dependent on transaction complexity)
  • Average latency: 2-5 seconds per transaction (includes GUI rendering)
  • Scales poorly - each bot requires full SAP GUI instance (200-300MB memory)
  • For 800/hour peak, you’d need 15-20 concurrent bot instances
  • Network latency significantly impacts performance

For your 5,000 daily transactions (208/hour average, 800/hour peak), native connectors can handle the load with 3-4 connections during average periods and 8-10 during peaks. RPA bots would require 10-20 instances, which is expensive both in infrastructure and licensing.

Maintenance Requirements:

Native Connectors:

  • Initial development: Higher (4-8 weeks for 15 transaction types)
  • Requires SAP technical skills (ABAP knowledge helpful but not mandatory)
  • Maintenance: Low - typically 2-4 hours/month
  • SAP upgrades: Minimal impact (APIs are stable across versions)
  • Changes needed only when: Adding new fields, new transaction types, or SAP customization changes
  • Our clients average 8-12 hours/year maintenance time

RPA Bots:

  • Initial development: Lower (2-4 weeks for 15 transaction types)
  • Requires UI automation skills (easier to find)
  • Maintenance: High - typically 8-16 hours/month
  • SAP upgrades: High impact (every GUI change breaks bots)
  • Must update when: Screen layouts change, new fields added, workflow changes, SAP patches applied
  • Our clients average 80-120 hours/year maintenance time

Recommendation for Your Scenario:

Given your volume (5,000/day) and transaction variety (15 types), I recommend a tiered approach:

Tier 1 (80% of volume, 8-10 transaction types): Native RFC connectors

  • Standard transactions: Purchase orders, goods receipts, invoice verification
  • Use standard BAPIs: BAPI_PO_CREATE, BAPI_GOODSMVT_CREATE, etc.
  • Estimated development: 6 weeks
  • Expected throughput: 200+ transactions/minute

Tier 2 (15% of volume, 3-4 transaction types): Hybrid approach

  • Semi-standard transactions with some custom fields
  • Use RFC to call custom function modules you create in SAP
  • Estimated development: 3 weeks

Tier 3 (5% of volume, 2-3 transaction types): RPA bots

  • Truly custom screens without API alternatives
  • Complex approval workflows requiring human-like navigation
  • Estimated development: 2 weeks

Implementation in integration-hub:

  1. Create a transaction router that classifies incoming requests
  2. Route to appropriate connector type based on transaction code
  3. Implement unified error handling and retry framework
  4. Build monitoring dashboard showing success rates by connector type
  5. Set up alerts for throughput degradation or error rate spikes

This hybrid approach gives you 95%+ of the performance benefits of native connectors while maintaining flexibility for truly custom scenarios. Total development time: 11 weeks. Ongoing maintenance: estimated 15-20 hours/month initially, dropping to 8-12 hours/month after stabilization.

The key success factor is having clear routing logic and not defaulting to RPA when a native connector would work with slightly more upfront effort.