Alphyn Lakehouse

Lakehouse Use Cases

Proven deployment scenarios across finance, retail, insurance, and industrial sectors — backed by 15+ production deployments

Deployment Scenarios

Six Ways Enterprises Deploy Alphyn Lakehouse

Legacy MPP Migration

Replace legacy MPP databases with a modern lakehouse that delivers 2–5x faster ingestion on a fraction of the hardware. Built-in procedural SQL accelerator enables smooth migration of stored procedures and business logic.

2–5x faster than legacy MPP
2–4x lower total cost of ownership
Procedural SQL for PL/SQL and T-SQL compatibility

Real-Time Data Hub

Capture every change in milliseconds with built-in CDC streaming. Process complex events with windowed aggregations, stream joins, and real-time enrichment — then land results directly into Iceberg tables.

Sub-second CDC event capture
Complex event processing built in
Visual low-code pipeline editor

Ad-Hoc Analytics at Scale

Give analysts elastic compute that scales during peak workloads. Multiple query engines mean the right tool for each job — sub-second dashboards alongside complex ad-hoc exploration on the same data.

Elastic compute resources
Sub-second BI on materialized views
Self-service analytics with unified security

Sovereign Data Platform

Deploy on-premises, in any cloud, or fully air-gapped. Data never leaves infrastructure you control. Optional FIPS 140-3 compliance, WORM storage, and multi-site disaster recovery for the most demanding regulatory environments.

Air-gapped deployment capable
FIPS 140-3 and WORM compliance
Multi-site disaster recovery

Unified Data Platform

Consolidate streaming, batch replication, analytics, ML, and governance onto a single Kubernetes-native platform. Eliminate tool sprawl and data silos with one unified metadata layer across all engines.

Single metadata layer across all engines
Streaming + batch + analytics unified
One security framework for everything

ML & Data Science Factory

Interactive notebooks with native lakehouse data access, distributed model training, and high-speed Arrow-based data connectivity. Build models directly on production data — no copies, no movement, no delays.

Native Arrow-based data connectivity
Interactive notebooks on live data
Seamless path to production pipelines

Customer Case

Legacy MPP Replacement

Alphyn Lakehouse vs. Legacy MPP — real benchmark results

2–5x
Faster Ingestion

Reducing ETL windows from hours to minutes

3x Less
CPU & Memory

Commodity K8s nodes instead of dedicated MPP appliances

70%
Direct SQL Translation

Legacy stored procedures migrated via procedural SQL accelerator

Test Scenario

Loading a massive dataset (10TB+) to simulate daily batch processing windows, with concurrent analytical queries running alongside.

Migration Approach

Procedural SQL accelerator handled ~70% of stored procedures with direct translation, 20% with minor adaptation, and 10% requiring targeted refactoring.

Discuss Your Migration

Industries

15+ Production Deployments Across Regulated Sectors

Financial Services

Real-time fraud detection, risk analytics, regulatory compliance, and legacy core banking migration

Retail & E-commerce

Customer 360, real-time personalization, inventory optimization, and omnichannel analytics

Insurance

Claims analytics, actuarial modeling, and regulatory reporting on sovereign infrastructure

Industrial & Energy

IoT data processing, predictive maintenance, and operational analytics at petabyte scale

Ready to See Alphyn Lakehouse in Action?

Get a hands-on assessment of how Alphyn Lakehouse fits your specific workload and infrastructure.