The infrastructure decision your IPMS will live with for a decade
Research data isn’t growing incrementally — it’s compounding. The architectural choices made when selecting an IPMS determine whether your system keeps up, or holds you back.
Exponential growth is already here
If you projected your office’s data needs over the next ten years, would you expect them to grow linearly — or compound? Every major trend points to the same answer.
AI & Machine Learning
Model training, inference logs, and research datasets grow faster than any other category.
Research Data Expansion
Disclosure volume, lab outputs, and experimental data sets are increasing year over year.
IoT & Lab Sensors
Connected devices and instrumentation generate continuous, high-frequency data streams.
Cloud-Based Systems
Migration to cloud platforms increases storage and transfer demands across every workflow.
Real-Time Analytics
Reporting expectations have shifted from monthly exports to live dashboards and instant queries.
Digital Collaboration
Cross-institutional workflows, partner portals, and external integrations expand the data surface.
None of these trends are slowing down — they are compounding. The question for your IPMS isn’t whether data demands will grow. It’s whether your infrastructure is built to handle it.
Two models. One critical difference.
When evaluating an IPMS, features and UI get most of the attention. The architecture underneath rarely does — until it becomes a problem.
Single-Tenant
Minuet Architecture
- Your institution has a fully dedicated environment
- Compute resources are never shared with other customers
- Data is completely isolated — no co-mingling
- Performance is consistent and predictable at any volume
- Scales independently based on your actual needs
- Upgrades are controlled within your environment
Multi-Tenant
Shared Platform Model (e.g., Salesforce-based)
- Multiple institutions share the same infrastructure
- Resources are pooled and dynamically allocated
- Performance is influenced by other tenants’ activity
- Subject to platform-wide API limits and throttling
- Scalability is tied to platform constraints
- Platform updates affect all tenants simultaneously
Performance at scale, head to head
At small data volumes, the differences feel abstract. As your research activity grows, they become mission-critical.
| Category | Single-Tenant (Minuet) | Multi-Tenant (Salesforce-based) |
|---|---|---|
| Performance Consistency | Dedicated resources — stable, predictable performance | Can fluctuate due to “noisy neighbor” effect |
| Resource Contention | No competition — resources fully allocated to you | Competes with other tenants, especially during peak periods |
| Platform Limits | No shared API or query limits | Bound by API limits, query constraints, and processing caps |
| Scalability | Scales independently based on your data and usage | Scalability tied to platform constraints and shared infrastructure |
| Performance Over Time | Remains consistent as data volume grows | Can degrade as data volume and customization increase |
| Upgrade Impact | Controlled, predictable upgrades within your environment | Platform-wide updates can introduce variability or disruption |
| Customization Impact | Optimized for your workflows without performance cost | Heavy customization increases complexity and slows performance |
| Data Operations | High-volume reporting and integrations without constraints | Large queries often require workarounds or optimization |
| Risk Profile | Lower — performance issues are isolated and controllable | Higher — affected by platform health, limits, and external factors |
| Operational Burden | Less ongoing effort to maintain performance | Requires continuous monitoring, tuning, and workaround strategies |
What multi-tenant systems don’t advertise
These patterns appear consistently at institutions running Salesforce-based IPMS platforms at scale.
Performance variability under load
Slower response times during peak periods when multiple tenants compete for the same resources — often at the exact moment your team needs the system most.
API & query limits
Platform-enforced caps mean large integrations, reporting runs, and data syncs must be broken into smaller operations — adding delays and failure points.
Shared infrastructure dependency
Your system’s behavior is partially determined by what other tenants are doing. You have less control over your own environment than you may realize.
Compounding complexity over time
As customization depth increases, multi-tenant systems become harder to maintain and upgrade — creating a growing operational burden over a 5–10 year horizon.
Infrastructure that earns your confidence
An IPMS is not a short-term software decision — it’s long-term institutional infrastructure. When evaluating systems, don’t just ask what the platform can do. Ask how it will perform years from now.
- ✓ High, consistent performance independent of other institutions’ workloads
- ✓ No shared constraints — your data volume is your only limit
- ✓ Scalability aligned to your institution’s growth, not a vendor’s roadmap
- ✓ Reduced long-term operational burden — less monitoring, fewer workarounds
- ✓ GovRAMP Moderate and TX-RAMP Level 2 authorized — FedRAMP on roadmap
“Inteum is our system of record. Even Workday cannot hold the level of granularity we get from Minuet.”Johns Hopkins UniversityTechnology Transfer Office · AI Workshop, May 2026
Performance isn’t just speed. It’s institutional continuity.
See how Minuet’s single-tenant architecture handles your institution’s specific workload requirements — now and over the next decade.
30+ years · 300+ customers · 30 countries