Cost-Optimized Cloud Analytics Modernization

Datalite helps organizations modernize expensive, proprietary cloud data warehouse and analytics platforms with an open, scalable, and high-performance architecture built on Airbyte, Apache Beam/Spark, Apache Iceberg, Apache Doris, Apache Airflow, and Amazon S3.

Our solution provides a practical replacement path for cloud-based proprietary analytics platforms by separating storage, compute, ingestion, orchestration, and serving layers. This approach enables customers to reduce long-term platform costs, improve query performance, avoid vendor lock-in, and maintain greater control over their enterprise data ecosystem.

Using Amazon S3 as the low-cost storage foundation and Apache Iceberg as the open table format, Datalite builds a reliable lakehouse layer that supports structured data, schema evolution, snapshots, and scalable analytics. Data ingestion is handled through Airbyte, complex processing is performed using Apache Beam or Spark, and workflow orchestration is managed through Apache Airflow. For high-speed analytics and serving, Apache Doris provides fast SQL performance for dashboards, ad-hoc querying, reporting, and data science workloads.

This architecture combines the flexibility of a data lake, the reliability of a warehouse, and the performance of a modern analytics engine—without forcing customers into a single proprietary platform.

Datalite’s Cost-Optimized Cloud Analytics Modernization service is ideal for organizations seeking to reduce data warehouse costs, modernize legacy ETL environments, support high-volume data processing, improve dashboard performance, and build an open standards-based foundation for business intelligence, machine learning, regulatory reporting, and enterprise analytics.

With deep experience in cloud data engineering, healthcare data platforms, federal reporting, interoperability, and data quality frameworks, Datalite delivers production-ready analytics solutions that are secure, scalable, governed, and cost-efficient.