Modern Data Platform · By SelarasTech

The modern data platform that runs on your terms

Cradlehouse unites ingestion, lakehouse storage, transformation, governance, and analytics on one backbone — built on open Apache Iceberg tables, powered by a ClickHouse OLAP engine, and deployable on-premise, in the cloud, or hybrid.

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Open formats. No proprietary lock-in. Controls that map to GDPR and Indonesia's Personal Data Protection Law (UU PDP).

Most "data stacks" are five tools pretending to be one

Ingestion in one product. Transformation in another. A catalog nobody has updated since the pilot. Dashboards querying a warehouse whose bill grows every quarter. And when someone asks where a number came from, the answer takes three days and a chain of emails.

Cradlehouse replaces the stitching. One multi-tier platform — ingestion, processing, storage, and serving — on a single governed backbone.

Architecture Deck

A single backbone for the whole data lifecycle

Cradlehouse features a multi-tier architecture based on a centralized data repository — encompassing ingestion, processing, storage (lakehouse), and serving layers. The result is integrated, scalable, end-to-end data management that's ready for advanced analytics from day one.

Sources & Ingestion

Cradlehouse ingests from across your estate, whatever shape it arrives in. Scheduled batch loads and near real-time streams land in the same platform on a governed path. Incremental sync moves only what changed to reduce processing resource spikes.

Structured (MySQL, Postgres, Oracle)

Semi-structured (JSON, CSV)

Unstructured (PDFs, Docs)

Cloud / SaaS (S3, APIs)

The Lakehouse Stack (Bronze, Silver, Gold)

Data lands raw in Bronze, is conformed and deduplicated in Silver, and is presented as trusted, business-ready entities in Gold. Underneath, the Iceberg metadata layer handles table creation, snapshot management, and schema evolution automatically.

Processing & Serving via ClickHouse Core

A column-oriented, distributed OLAP core handles heavy aggregations and keeps multidimensional queries returning sub-seconds as storage scales. Open storage definitions mean you can also query via Trino or Dremio easily.

Cradlehouse Multi-tier Architecture Blueprint

Fig 1.1 — Integrated Topology Plan P0 Tier Spec

Unified Workspace

One workspace for querying, scheduling, visualizing, and governing

SQL console, pipeline design UI, metadata charts, and automated cron rules within a single product profile. No tool switching required.

SQL Console

A fast, intuitive interface to explore tables, write optimized scripts, and review schema states directly on active engines.

Pipeline Builder

Cleanse, join, and model datasets via low-code node setups. Track processing paths and dependency workflows without complex scripting setups.

Schedules & Monitoring

Manage run automation, view real-time log histories, and establish proactive alerting boundaries for background processing cycles.

Brain (AI Workflows)

An integrated assistant built specifically to parse operational contexts, offering query correction and translation steps natively.

Security & Deployment

Deploy it where your regulator says it has to live

On-premise infrastructure, private cloud arrays, or hybrid topologies. The platform architecture adapts cleanly without modifying control layers.

Infrastructure Options

Deploy via orchestrated Kubernetes setups or isolated container runtimes directly on bare-metal and VM options where cloud footprints are prohibited.

Identity Governance

Leverage standard identity synchronization methods out of the box. Includes native single sign-on parameters via Keycloak and enterprise LDAP setups.

Compliance Footprint

Cradlehouse supports structural architectures required to align configuration data with requirements under GDPR and Indonesia's Personal Data Protection Law (UU PDP).

Built for scale, governed by default, ready for AI

Scalable Cloud Datacenter Infrastructure

Scale without surprises

A centralized, multi-tier architecture spanning ingestion, processing, storage, and serving — engineered for high availability and predictable cost.

Data Privacy Governance and Security Dashboard

Governance by default

Data catalog, lineage, access control, and data quality are built in and reinforced by role-based access control and encryption.

Machine Learning Algorithms and Prediction Code

From reporting to prediction

Integrated analytics and ML — with Apache Spark support for custom models — help teams read behavioral patterns and sharpen targeting.

Supported Integrations & Infrastructure

Get Started

Let's look at your actual data problem

Tell us what you're running today. We'll show you what Cradlehouse does about it — on your architecture, not a generic snapshot dataset.

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