Avocado Datalake offers comprehensive data ingestion and management solutions designed to streamline the creation of data lakes and data warehouses across major cloud providers like AWS, GCP, and Azure. The platform provides ready-to-use, scalable codebases for ingesting structured, semi-structured, and unstructured data sources into centralized data lakes, supporting formats such as Apache Iceberg, Hudi, Delta Lake, and XTable. It enables organizations to efficiently extract data from RDBMS, NoSQL, and file-based sources, transforming and loading it into cloud storage and data warehouses like Redshift, BigQuery, and Snowflake.

• Supports ingestion from RDBMS, NoSQL, and unstructured data sources
• Provides scalable ETL pipelines for data lake and warehouse synchronization
• Integrates with centralized data catalogs and access control systems
• Compatible with multiple cloud providers and open table formats

How it works: The platform offers configurable pipelines that extract data from various sources, transform it as needed, and load it into centralized data lakes or warehouses. It includes support for open data formats and catalog interoperability, ensuring easy discovery and secure access control. The solution is designed for data engineers, data scientists, and BI teams seeking efficient data management and analytics infrastructure.

Pricing is flexible, with options for free, freemium, or paid plans, depending on organizational needs. The platform is ideal for enterprises looking to accelerate their data lake and warehouse setup, improve data accessibility, and enable advanced analytics and machine learning applications.