Amoro builds lake-native data warehouse and architecture for users, platforms and products
Continuously optimizing tables, including compacting small files, change files, regularly delete expired files to keep high query performance and reducing storage costs.
Support different table formats such as Iceberg, Paimon, Mixed-Iceberg and Mixed-Hive to meet different scenario requirements and provide them with unified management capabilities.
Provide an unified catalog service for all computing engines, which can also used with existing metadata store service such as Hive Metastore and AWS Glue.
Provide various plugins to integrate with other systems, like continuously optimizing with Flink and data analysis with Spark and Kyuubi.
Provide a variety of management tools, including WEB UI and standard SQL command line, to help you get started faster and integrate with other systems more easily.
Can be easily deployed and used in private environments, cloud environments, hybrid cloud environments, and multi-cloud environments.