Nuestro Arkham Data Lakehouse es el motor de alto rendimiento que sustenta toda la Plataforma de Datos. Combina la enorme escala de un data lake con la confiabilidad y rendimiento de un data warehouse, creando una base única y unificada para todos tus datos. Como creador, no gestionas el Lakehouse directamente; en cambio, experimentas sus beneficios a través de la velocidad, confiabilidad y potentes funciones de la cadena de herramientas de Arkham.
Nuestra arquitectura Lakehouse es el “cómo” detrás de la experiencia fluida que tienes en las herramientas UI de nuestra plataforma. Cada característica técnica fundamental del Lakehouse está diseñada para habilitar directamente una parte clave de tu flujo de trabajo.
Pipeline Builder
job runs a multi-stage pipeline, it executes as a single, atomic transaction. This means a pipeline either succeeds completely or fails cleanly, eliminating the risk of partial updates and data corruption, ensuring your Production datasets are always consistent.Playground
are fast because the Lakehouse uses open columnar formats (like Apache Parquet) and a decoupled compute architecture. Data is stored in a query-optimized way, and the query engine can scale independently, ensuring consistently low latency for your ad-hoc analysis, even on massive datasets.Data Catalog's
governance features. Every change to a dataset creates a new version, and the Catalog maintains a full, auditable history. This allows you to inspect the state of your data at any point in time, track lineage, and debug with confidence.Connectors
can reliably ingest data of any shape because the Lakehouse is built to handle any data format on cost-effective object storage, while the transactional layer still enforces strong schema validation on write. This unique combination gives you the flexibility of a data lake with the guarantees of a warehouse, right from the first step of your workflow.Para apreciar los beneficios del Lakehouse gestionado de Arkham, es útil compararlo con las arquitecturas tradicionales que los equipos de datos suelen tener que construir y mantener por sí mismos. La plataforma de Arkham está diseñada para ofrecerte las ventajas de un Lakehouse sin la complejidad de configuración y gestión.
Feature
Data Lakes
Data Warehouses
Arkham Lakehouse (Best of Both)
Storage Cost
✅ Very low (S3)
❌ High (compute + storage)
✅ Very low (S3)
Data Formats
✅ Any format (JSON, CSV, Parquet)
❌ Structured only
✅ Any format + structure
Scalability
✅ Petabyte scale
❌ Limited by cost
✅ Petabyte scale
ACID Transactions
❌ No guarantees
✅ Full ACID support
✅ Full ACID support
Data Quality
❌ No enforcement
✅ Strong enforcement
✅ Strong enforcement
Schema Evolution
❌ Manual management
❌ Rigid structure
✅ Automatic evolution
Query Performance
❌ Slow, inconsistent
✅ Fast, optimized
✅ Fast, optimized
ML/AI Support
✅ Great for ML
❌ Poor ML support
✅ Great for ML
Real-time Analytics
❌ Batch processing
✅ Real-time queries
✅ Real-time queries
Time Travel
❌ Not available
❌ Limited versions
✅ Full version history
Setup Complexity
✅ Simple (but lacks features)
❌ Complex ETL
✅ Zero (Managed by Arkham)