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Target customers: customers who need to store cold and hot data separately. Data delivery uses the time to live (TTL) feature of Tablestore to store full data in OSS at low cost while Tablestore provides query and analysis of hot data with low latencies Full data backup You can use data delivery to deliver data of a whole table from Tablestore to an OSS bucket to back up and archive the data. Large-scale real-time data analysis You can use data delivery to deliver incremental data from Tablestore to OSS in real time (every 2 minutes). Delivered data is partitioned based on the system time and stored in the Parquet format. In addition, you can use OSS high-speed bandwidth to read data and optimize the process used to scan Parquet data. This way, efficient real-time data analysis is implemented. Accelerated analysis by using SQL statements When search indexes are not created for Tablestore data, and the query conditions exclude primary key column-based filter conditions, you can use data delivery to synchronize data to OSS. Then, use DLA and OSS data scanning to accelerate SQL-based analysis. Released features: 1. Data delivery obtains full and incremental data of Tablestore. When the amount of data reaches the predetermined size or after the data is delivered for more than 2 minutes, the data is stored in OSS. 2. Data delivery allows you to deliver data in the following modes: incremental, full, and differential. The delivered data is stored in the Parquet format. 3. Data delivery allows you to monitor the time when data delivery is complete. Data delivery provides the DescribeDeliveryTask operation to return the time when data delivery is complete.