In scenarios such as computing analysis, backup archiving, and data import, ApsaraDB for Lindorm (Lindorm) allows external systems to directly access the underlying files of multiple engines. This makes data reads and writes more efficient. For example, you can create physical files in the data format used in an offline computing system. Then, you can import the files into LindormDFS to mitigate the adverse impact on online services.
LindormDFS provides a distributed file storage system to store a large amount of unstructured data. LindormDFS shares storage with the other engines provided by Lindorm. The core capabilities of LindormDFS are supported by LindormDFS. LindormDFS optimizes object storage and block storage benefits. Object storage provides benefits such as low cost and high reliability. Block storage provides benefits such as high performance. In addition, LindormDFS uses techniques such as high-speed and low-speed tiered storage and intelligent data tiering. These techniques allow for LindormDFS that is fully compatible with Hadoop Distributed File System (HDFS) to provide you with the native capabilities of an elastic cloud for big data storage at low costs. You can use open source HDFS clients to directly access LindormDFS.
Low cost: The lowest unit price is CNY 0.12/GB/month. The unit price may vary by region. If the unit price is different, the unit price on the buy page prevails.
File system base: supports high-performance read and write operations on metadata. Files can be moved in batches by directory.
HDFS protocol compatibility: You can use open source HDFS clients to access LindormDFS without the need to worry about vendor lock-in. LindormDFS is compatible with a range of open source and Alibaba Could services, such as Hive, Spark, Impala, Presto, Flink, Yarn, Kylin, E-MapReduce (EMR), Data Lake Analytics (DLA), and MaxCompute.
Compute-storage separation: You can purchase storage capacity based on your business requirements. Computing is decoupled from storage. Therefore, you do not need to worry about the resource waste that is caused when storage is coupled to computing.
Hot and cold data storage: Hot and cold data can be stored in the same system. You can specify your data as hot data or cold data by file or folder. You can use a high-cost storage medium to store hot data and use a low-cost storage medium to store cold data. This way, costs can be reduced.