The "Compute-to-Data" Engine

Don’t copy the
data. Control the execution.

The experts for mission-critical infrastructure.
Federated execution. Kafka-based streaming. Distributed AI systems. Zero-copy architectures built for production, not slides.

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Data Processed (In-Place) 0 GB

Network Transfer (Minimized) 0 KB

Scalytics Federated Wayang Core

System Ready

Postgres SQL Engine

Spark Batch Processing

Flink Stream Engine

TensorFlow ML Inference

Live AI. Real-Time Decisions. High-Impact Results.

Own Your AI + Data Advantage.

Expert consulting from Apache Wayang PMC members, Kafka and Data Lakehouse Experts.

Start with an AI Audit →How It WOrks

Federated Intelligence for Governed, Distributed Data & AI

Execute analytics, feature engineering, and inference where data lives - reduce ETL, replication, and broken governance. Built by engineers with long-standing contributions to open, community-governed data processing systems.

Why Centralized Data Architectures Fail at Scale

Modern data estates are inherently distributed across clouds, regions, platforms, and operational systems. Centralizing all data into a single lakehouse introduces structural bottlenecks that compound as scale, velocity, and organizational complexity increase.

Data gravity and cost. Moving large datasets is slow, expensive, and increasingly unjustifiable.
Governance Drifts. Copies break lineage, access controls, and auditability.
Latency mismatch. Analytics and AI decisions lag behind operational reality.

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Regulatory, sovereign, and on prem constraints do not create these issues. They simply remove the option to ignore them.

Scalytics Federated - Built for Every Data Platform

On prem and edge sources connect to Scalytics Federated. Integrate with any Iceberg and Data Lakehouse, including Unity Catalog, workflows, and notebooks.

Execute locally:
Stream approved results and lineage back to your warehouse or lakehouse while your central catalog remains the policy authority.
Return what’s allowed:
Push features, metadata, and model outputs into your Data Lakehouse for analytics and machine learning. No raw sensitive data leaves restricted zones.
Govern once:
Define policies centrally in Iceberg REST / Unity Catalog. Local execution enforces them automatically.

The Virtual Data Lakehouse

Unified Access. Decentralized Storage.

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Warehouses Snowflake / BigQuery

☁️

Object Storage AWS S3 / ADLS / GCS

🗄️

Databases PostgreSQL / Oracle

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Federation Layer

Scalytics Federated

The Apache Wayang optimizer plans queries across systems without moving data.

⚡ Cost-Based Optimizer

🔒 Privacy Filters

🌐 Cross-Platform Join

🛡️ Governance / RBAC

➜

Single SQL Interface

Treat your entire landscape as one database.

Tableau Jupyter Apps

✅ No ETL Pipelines Required

Deployment Options for Scalytics Federated: Your private cloud, on-premises, or hybrid. You own the models, the data, and the intelligence.

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The Scalytics Model: Strategy Before Technology

Most data and AI initiatives fail because they start with tools instead of architecture. Consultants deliver reports without execution. Vendors ship software without understanding operational constraints.

We work end to end. We map your data logic, align governance and compliance, then build, measure, and scale with you. No handoffs. No surprises.



Regulated Data in AI Pipelines

Keep sensitive and operational data in sovereign locations. Stream compliant features and signals into Databricks for model training, monitoring, and evaluation—no replication, no compliance risk.

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Low-Latency Feature Serving

Generate and serve real-time features directly at the edge. Databricks consumes consistent data without duplication, ensuring synchronized batch and streaming pipelines across all environments.

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Cross-Region Data Processing

Unify insights across distributed regions using federated results in Delta-friendly formats. Full visibility in Unity Catalog with governance and lineage built directly into execution.

Proven High-ROI Use Cases

Scalytics Federated Intelligence brings secure, compliant, and high performance data processing to distributed and hybrid environments.

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Federated Feature Engineering

Build and serve machine learning features across on prem, private, and sovereign data without moving raw datasets. Stream compliant features into your training and monitoring stack.

Impact: Faster feature delivery, no replication risk, and consistent compliance across data domains.

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Real-Time Model Inference

Execute inference directly where data is generated at the edge, in sovereign clouds, or in enterprise datacenters. Sync results and lineage back to your analytics platform for unified visibility.

Impact: Lower latency, reduced network overhead, and consistent performance across hybrid architectures.

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Cross-Cloud Analytics & Governance

Unify on prem, cloud, and regulated environments through federated query execution at the source. Sync governed results and full lineage back to your central platform for operational visibility.

Impact: End-to-end transparency, consistent governance, and faster collaboration across distributed teams.

Why Companies Choose Us

Deep Data + AI Expertise

We’ve built and deployed federated AI for critical industries. We bridge Databricks, Confluent, and enterprise data systems to build real-time operations.

Strategy + Implementation

We don’t just define blueprints. We integrate Scalytics with your Databricks environment, deploy pilots fast, and scale proven ROI-driven workloads.

Measured ROI + Excellence

Every project defines KPIs from day one — latency reduction, compliance alignment, or cost optimization. Measured outcomes, not slideware. That's our DNA.

Start with a Federated Intelligence Strategy

4–6 week deep dive: hybrid data assessment, federated architecture design, and ROI modeling. Includes a full readiness review and a step-by-step roadmap for secure, measurable implementation.