This topic describes the editions of ApsaraDB for HBase and how to select an edition.
ApsaraDB for HBase Standard Edition
Based on the open source HBase, ApsaraDB for HBase Standard Edition enables custom features and optimizes service stability and O&M. ApsaraDB for HBase optimizes services by using the following methods:
Optimize ApsaraDB for HBase Performance-enhanced Edition.
Release patch files of new editions in the open source community.
Fix bugs that are identified during testing and production to improve user experience.
The custom features supported by ApsaraDB for HBase are portable across versions. When a new community edition is released, Alibaba Cloud can develop an upgraded version of ApsaraDB for HBase based on the new community edition at the earliest opportunity. By using a comprehensive internal testing and regression system, Alibaba Cloud ensures that you can use the latest and comprehensive features that have high stability and improved capabilities. ApsaraDB for HBase Standard Edition supports two versions: V1.1 and V2.0. These versions are based on the open source HBase V1.1.2 and V2.0.0, respectively. ApsaraDB for HBase Standard Edition is 100% compatible with the open source HBase.
ApsaraDB for HBase Performance-enhanced Edition
ApsaraDB for HBase Performance-enhanced Edition is a cloud-hosted database developed based on Lindorm. This edition is fully compatible with the open source HBase and has been used to store large amounts of Alibaba internal business data for more than 10 years. It supports a large number of core applications such as Taobao, Alipay, Cainiao, Youku, and AMAP. Compared with the HBase community edition, ApsaraDB for HBase Performance-enhanced Edition provides enterprise-level capabilities and more benefits in terms of costs, performance, stability, features, security, and usability. You can connect to ApsaraDB for HBase Performance-enhanced Edition by using the official client or standard API. This edition supports the clients of ApsaraDB for HBase V1.x and V2.x. ApsaraDB for HBase Performance-enhanced Edition is almost 100% compatible with the open source HBase in terms of the features and service API. ApsaraDB for HBase Performance-enhanced Edition delivers up to seven-fold performance of the open source HBase at half of the storage cost. For more information, see Benefits.
Select an edition
ApsaraDB for HBase Performance-enhanced Edition is industry-leading in terms of maturity, scale, and cost-effectiveness. It also provides enterprise-level features and management tools, and has been tested by the core services of Alibaba Group. ApsaraDB for HBase Performance-enhanced Edition is ideal for general enterprise customers.
Based on the open source HBase, ApsaraDB for HBase Standard Edition enables custom features and optimized services. It is ideal for scenarios where the performance-enhanced edition fails to meet your custom needs.
ApsaraDB for HBase Serverless Edition is a serverless service that is suitable for low-cost learning and testing scenarios.
ApsaraDB for HBase Performance-enhanced Edition supports common big data ecosystems such as Hadoop Distributed File System (HDFS), Spark, Hive, and OpenTSDB but does not support Phoenix. It does not support some components such as Kylin and Geomesa. These features will be available in later versions. ApsaraDB for HBase Performance-enhanced Edition is compatible with the open source HBase in terms of the features and the service API. The kernel of ApsaraDB for HBase Performance-enhanced Edition uses the Lindorm wide table engine. For more information about enterprise-level features such as SQL support and high-performance native secondary indexes, see Lindorm.
Feature comparison between editions
In the following table, 
indicates that the feature is supported and 
indicates that the feature is not supported.
Feature | HBase edition | ||
ApsaraDB for HBase Performance-enhanced Edition | ApsaraDB for HBase Standard Edition | HBase Open Source Edition | |
Performance optimization |
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Global secondary index |
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Full-text search (compatible with Solr) |
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Hot and cold data separation |
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Enterprise-level backup |
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Active/standby disaster recovery |
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Active-active redundancy |
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Strong consistency across data centers |
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Smart diagnosis and management |
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Big data ecosystem |
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