Amoro builds lake-native data warehouse and architecture for users, platforms and products
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Key Features
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Continuously optimizing tables, including compacting small files, change files, regularly delete expired files to keep high query performance and reducing storage costs.
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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.
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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.
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Provide various plugins to integrate with other systems, like continuously optimizing with Flink and data analysis with Spark and Kyuubi.
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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.
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Can be easily deployed and used in private environments, cloud environments, hybrid cloud environments, and multi-cloud environments.