Performance

Performance That Scales

Real benchmarks against real competition. Every number independently reproducible.

Test Environment

Both systems tested on identical hardware: 8 vCPUs, 16 GB RAM. 50 queries per thread across 12 concurrency stages (1 to 128 threads). Zero failures across all test runs. March 2026.

Standard MDX SELECT

Large result-set retrieval across profit centers, time periods, and scenarios.

Single thread
Ardello
48ms
SSAS
185ms
128 threads
Ardello
169ms
SSAS
5,912ms
35x faster

TOPCOUNT Analytical Query

Top-20 ranking over a large member set. Measures analytical computation under concurrency.

Single thread
Ardello
45ms
SSAS
51ms
128 threads
Ardello
439ms
SSAS
1,844ms
4.2x faster

Why the Architecture Matters

Ardello uses persistent WebSocket connections, one socket per client, kept alive for the session. SSAS uses ADOMD.NET over TCP with a new connection per query. At low concurrency, the difference is modest. At 128 threads, connection management overhead dominates SSAS response times. This is not a tuning problem; it is an architectural ceiling.

Degradation Under Load

The most revealing metric is not absolute speed; it is how gracefully a system degrades as concurrency increases.

3.5x
Ardello degrades 3.5x from single-thread baseline at 128 concurrent threads.
32x
SSAS degrades 32x from single-thread baseline at 128 concurrent threads.

Effective Throughput

Ardello achieves 36.6x throughput scaling on Test A compared to SSAS's 4.0x, a 9x advantage in effective throughput. Even with the more demanding TOPCOUNT query, Ardello delivers 13.2x throughput scaling vs SSAS's 3.5x.

36.6x
Ardello (Test A)
4.0x
SSAS (Test A)
13.2x
Ardello (Test B)
3.5x
SSAS (Test B)

Where Ardello Fits

Every existing option solves only part of the problem. Legacy OLAP engines like SSAS are genuinely multidimensional but stay tied to on-premise infrastructure. Cloud columnar engines like ClickHouse scale effortlessly but speak only SQL. Semantic layers like AtScale exist to patch the limitations of SQL-based solutions, layering multidimensional modeling on top of a warehouse without an engine of their own. BI tools like Power BI ship polished reports but model data in flat tables, not true cubes. Ardello is the only platform that unites a native multidimensional MDX engine with cloud-native, browser-direct delivery.

CapabilityArdelloSSASClickHouseAtScalePower BI
Native MDX Engine Translates DAX-first
True Multidimensional Modeling Virtual
Near-Instant Round-Trip Varies DW-bound
On-the-fly DB Provisioning Managed
WebSocket Delivery
Dev / Test / Prod Premium
Integrated Report Builder
Model / Report Separation N/A N/A Partial

Test: 50 queries per thread × 12 concurrency stages (1–128 threads). 8 vCPUs, 16 GB RAM. Zero failures. March 2026.

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