AI Raises the Bar for Data Infrastructure.
Data lag degrades model accuracy and real-time decisions.
Costs become unpredictable at scale.
When pipelines break, AI stops.
High‑velocity data overwhelms traditional stacks:
Manufacturing
Historians weren’t built for modern analytics:
limited computation, no scalability, no high-resolution data.
Petabyte-ready velocity.
Finance
Warehouses choke on billions of daily trades and quotes.
Costly Pipelines
up to 10–20× compression & upstream ingest.
Simulation
Petabyte-scale outputs overwhelm storage and pipelines.
Lack of Flexibility
SQL-native + distributed computing.

Where do I sit in your stack ?
The Quasar Difference
Quasar defines the operational numerical layer: purpose-built for sustained, high-volume numerical workloads. It delivers deterministic performance and predictable infrastructure economics for AI and advanced analytics.
Traditional stacks were not designed for this class of workload.
Resources & Insights
Case Study
Reducing Unplanned Downtime: How Quasar Helped Georgia-Pacific breakthrough data...

Whitepaper
Beneath the Surface: A Deep Dive into Quasar’s Real-Time Data Intelligence Platform (Part 2)

Whitepaper
Beneath the Surface: A Deep Dive into Quasar’s Real-Time Data Intelligence Platform (Part 1)
January 16, 2026
QuasarDB “Seneca” 3.14.2 Released
December 9, 2025
Engineering Reliability at Scale, Part 3 – Taking a Step Back
October 8, 2025
Beyond Unit Tests: Building Confidence in Complex Systems
July 30, 2025
Introducing the next generation of Quasar
July 8, 2025
Monitoring: Why Logs Matter More Than You Think
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