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Universal Semantic Layer : The foundation for instant, actionable, agentic analytics
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1000x Faster Analytics

Lightning-Fast Analytics
on Real Enterprise Workloads

Reliably fast analytics performance, even as data volumes,
users and complexity grow

Quick Read

  • Predictable performance under peak and mixed workloads
  • Works with your existing BI tools and data platforms
  • Scales to thousands of users without degradation
  • Stays fast even for deep, high-granularity analytics
  • Sustain performance without constant dashboard or infra tuning
Query Response Time
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Demo

Blazing fast Power BI on 100s of billions of rows

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The Performance Gap in Enterprise Analytics

As data volumes grow, users multiply and queries become more complex, performance breaks down, forcing teams to trade off responsiveness, cost and scale.

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    BI tools slow down as data volume and analytics complexity increase

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    Concurrency kills performance as more users run complex queries simultaneously

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    Every interaction hits the warehouse, slowing dashboards and increasing load

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    Performance is tied to warehouse size and workload, driving costly over-scaling

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    Drill-downs from KPIs to transaction-level data trigger slow, expensive computations

Make every BI experience feel instant

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    Dashboards load fast, even at peak concurrency

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    Filters, pivots and drill actions stay responsive

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    No more “dashboard is still loading” moments in meetings

Case Study

Enabling fast analytics across Power BI, Tableau and Excel for a global software leader

Read more Enabling fast analytics across Power BI, Tableau and Excel for a global software leader

Analytics without Data Plaftorm Bottlenecks

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    Eliminate repeated full data scans that slow queries

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    Avoid over-scaling warehouses just to maintain speed

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    Keep performance steady as data and workloads grow

Case Study

Powering Fast BI on Azure for 12B Retail Records

Read more Powering Fast BI on Azure for 12B Retail Records

Predictable performance under high concurrency

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    Instant responses under peak and concurrent usage

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    No sudden slowdowns due to user spikes or heavy queries

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    Performance holds during business-critical periods

Case Study

Sub-second responses on billions of rows for 1000s of concurrent users at a global telecom

Read more Sub-second responses on billions of rows for 1000s of concurrent users at a global telecom,

Speed without sacrificing analytical depth

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    Fast drilldowns from KPIs to transaction-level detail

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    Responsive slice-and-dice across many dimensions

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    No slowdown as data granularity increases

Case Study

Delivering store-level drill down across 9500+ outlets to a retail giant

Read more Delivering store-level drill down across 9500+ outlets to a retail giant

How Kyvos Fits in Your
Analytics Stack

Why Kyvos is your performance edge

A performance architecture built for concurrency, scale and complexity

  • AI-powered smart aggregation

    Automatically builds only the most useful data aggregates based on real usage and changing query patterns so that queries stay fast.

    AI-powered smart aggregation

  • No pushdown

    Executes analytics outside the warehouse, avoiding per-query pushdowns that slow performance and increase cost.

    No pushdown

  • Fully distributed and elastic architecture

    Scales out seamlessly across nodes to handle growing data, users and workloads without re-architecture.

    Fully distributed and elastic architecture

  • Columnar, vectorized processing

    Processes only needed data in efficient columnar batches, enabling faster scans and computations at scale.

    Columnar, vectorized processing

  • Self-tuning, disk-based caching with no in-memory constraints

    Dynamically optimizes caching on disk to sustain high performance without being limited by memory size.

    Self-tuning, disk-based caching with no in-memory constraints

  • AI-powered smart recommendation engine

    Continuously suggests optimal aggregates.

    AI-powered smart recommendation engine

  • Massively parallel GPU retrieval for AI

    Uses GPUs to retrieve and prepare data in parallel, delivering low-latency responses for AI and analytics workloads.

    Massively parallel GPU retrieval for AI

Our Impact

Responses in less than 5 seconds on 500 billion transactions at a global bank
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Global sports betting company migrates SSAS to Kyvos for deeper analytics
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Global fintech ends analytical silos with Kyvos
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Pharmacy chain delivers self-service analytics for 20,000+ suppliers
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FAQs

How does Kyvos deliver sub-second performance across all BI tools?
Kyvos provides consistently fast analytics across Tableau, Power BI, Excel, Looker and more. Queries are executed on Kyvos’ high-performance semantic layer, not inside individual BI engines, removing tool-specific performance limits.
How is Kyvos different from warehouse tuning or BI acceleration?
Kyvos delivers predictable performance across all queries, not just optimized ones. Instead of tuning SQL or accelerating individual queries, Kyvos removes the warehouse from the real-time execution path entirely.
What happens when thousands of users query data at the same time?
Response times remain consistent even during enterprise-wide, concurrent analysis. Kyvos uses a fully distributed, elastic architecture that isolates analytics execution from warehouse contention and scales independently of user concurrency.
How does Kyvos keep complex, multidimensional analysis fast?
Deep hierarchies, high-cardinality dimensions and large KPI sets stay fast at full analytical depth. Kyvos uses smart aggregation, self-tuning, disk-based caching and vectorized processing, eliminating runtime joins on raw data.
Why is “no pushdown” important for analytics speed?
Analytics remains fast and predictable without increasing warehouse load or cost. Kyvos executes analytics outside the warehouse, avoiding per-query pushdowns that trigger expensive scans and compete with other workloads.
How does Kyvos decide what to aggregate for performance?
Only the most valuable aggregates are created, keeping analytics fast. AI-powered smart aggregation analyzes query history, data profiles and usage patterns to recommend and adapt aggregates automatically.
Can Kyvos support both BI and AI workloads at speed?
BI dashboards and AI-driven analytics run with low latency on the same data foundation. Kyvos combines semantic execution with massively parallel GPU-based retrieval, enabling fast analytics without duplicating data.
Does Kyvos replace the data warehouse?
No—existing warehouses and lakehouses remain the system of record. Kyvos sits above them as a semantic layer, delivering speed without requiring data movement, re-platforming or architectural change.

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