PolarDB for PostgreSQL Enterprise Edition and Standard Edition offer different features. This topic compares them across 13 categories: cluster management, scalability, high performance, backup and restore, high availability, security, connection management, plugin management, GanosBase, cost-effectiveness, monitoring and optimization, PolarDB for AI, and data migration and synchronization. This helps you choose the right edition for your needs.
Feature comparison
PolarDB for PostgreSQL Enterprise Edition and Standard Edition are highly consistent in their core architecture and main features. This means you benefit from the core advantages of PolarDB regardless of which edition you choose. The performance differences between the two are mainly due to different software and hardware in the compute and storage layers. In the compute layer, Enterprise Edition uses physical machines for its compute nodes, which eliminates virtualization overhead. Standard Edition uses ECS servers. In the storage layer, you can view the performance comparison to check the maximum queries per second (QPS) data for different scenarios where clusters of the same specifications use different backend storage. The following table shows the feature differences between the two editions.
The limits for each feature depend not only on the product edition but also on other prerequisites. For example, serverless clusters (where the billing method is Serverless) only support PostgreSQL 14. For the prerequisites of each feature, see the specific feature description.
|
Category |
Features |
Description |
Enterprise Edition |
Standard Edition |
|
Cluster Management |
x86 architecture |
The x86 architecture uses Intel processors and high-performance networks. This improves overall performance and stability to meet the demands of enterprise applications that require high business stability and computing performance. |
Supported |
Supported |
|
YiTian ARM architecture |
The ARM architecture uses Alibaba Cloud's self-developed Yitian 710 processor chip and 25 GE intelligent high-speed network interface controllers (NICs). This provides powerful computing capabilities. |
Not supported |
Supported |
|
|
Clusters with one primary node and multiple read-only nodes |
PolarDB uses a distributed cluster architecture. A cluster contains one primary node and up to 15 read-only nodes, or just a single primary node. Multiple database nodes form the database engine layer. The primary node handles read and write requests, while read-only nodes handle only read requests. An active-active failover mechanism between the primary and read-only nodes provides a high-availability database service. |
Supported. Up to 15 read-only nodes. |
Supported. Up to 7 read-only nodes. |
|
|
The cluster recycle bin stores released PolarDB clusters. You can restore a cluster from the recycle bin to a new cluster, or delete the backup sets of a released cluster. |
Supported |
Supported |
||
|
After you create a PolarDB cluster, you can modify cluster and node parameters in the console. |
Supported |
Supported |
||
|
A PolarDB cluster has a three-layer architecture: the PolarProxy database proxy, the database kernel engine, and the distributed storage. You can upgrade the proxy or the kernel engine separately, or upgrade them together as needed. |
Supported |
Supported |
||
|
PolarDB for PostgreSQL provides a network channel management feature. Network channels let you access data across databases using methods such as foreign data wrappers (FDWs) and dblink. This makes cross-database access more flexible and convenient. |
Support |
Supported |
||
|
Scalability Management |
After you create a PolarDB cluster, you can manually add read-only nodes of the desired specifications or remove unneeded read-only nodes. |
Supported |
Supported |
|
|
PolarDB clusters support online configuration changes without locking the database. It supports three-dimensional scaling, and configuration changes take effect within minutes: vertical scaling of computing power, horizontal scaling of computing power, and horizontal scaling of storage space. |
Supported |
Supported |
||
|
Serverless is a dynamic scaling capability of the cloud-native database PolarDB. Nodes in a cluster can scale within seconds to handle sudden increases in business workloads without affecting your services. During periods of low business load, the mechanism automatically scales in to reduce costs. This is represented by clusters with the billing method set to Serverless. |
Not supported |
Supported |
||
|
Serverless is the dynamic elastic scaling capability of PolarDB. Each node in a cluster can elastically scale up within seconds to handle sudden workload surges without affecting ongoing operations, and automatically scale down during periods of low workloads to reduce costs. You can manually enable the Serverless feature for clusters that use the subscription or pay-as-you-go billing method. |
Supported |
Not supported |
||
|
High Performance |
The columnstore index complements the native PostgreSQL execution engine. Together, they allow PolarDB to retain high-performance transaction processing while significantly improving the performance of complex queries. |
Supported |
Supported |
|
|
Supports various SQL query optimization methods, such as pulling up correlated subqueries, plan freezing, cost-based query transformation, converting OR clauses to UNION ALL, and pushing down sub-joins. |
Supported |
Supported |
||
|
PolarDB partitioned tables are fully compatible with the syntax and features of native PostgreSQL. Compared to native PostgreSQL, PolarDB enhances performance and supports a rich set of partition types and combinations. This makes using partitioned tables more convenient, simple, and efficient. |
Supported |
Supported |
||
|
Provides a multi-tenant resource configuration feature to limit the resources used by one or more processes. This enables tenant-level resource limits. |
Supported |
Supported |
||
|
To reduce the frequency of calls to the file system, PolarDB for PostgreSQL implements a Relation Size Cache (RSC) in the storage management layer. It caches the number of blocks for a table in shared memory and updates the cache value when the number of blocks changes. Queries for the number of table blocks prioritize using the cache. This reduces requests to the file system and speeds up SQL execution. |
Supported |
Supported |
||
|
PolarDB for PostgreSQL lets you configure a maintenance window during off-peak business hours. It uses idle hardware resources during this period for active and thorough garbage collection. This reduces the frequency of automatic cleanups during peak hours, leaving more hardware resources for business read and write requests and optimizing read and write performance. |
Supported |
Supported |
||
|
Allows different connections to share the same Plan Cache. For applications with many different SQL statements, GPC can significantly reduce memory usage and the risk of out-of-memory (OOM) errors. The more efficient Plan Cache mechanism also reduces the overhead of generating execution plans, which improves performance. |
Supported |
Supported |
||
|
Global Cache is a collective term for the metadata caches in PolarDB for PostgreSQL that reside in shared memory and are shared by all processes. Global Cache allows all processes to share the same cache entry. This improves memory utilization and reduces the risk of OOM errors. |
Supported |
Supported |
||
|
Backup and Restore |
PolarDB supports data backups and redo log backups. A data backup generates a backup set of the full data of a cluster at a specific point in time, which is a full backup. A redo log backup records the incremental data generated after the backup set is created, which is an incremental backup. Using a full data backup and subsequent redo log backups, you can restore an entire PolarDB cluster or specific databases and tables to any point in time. |
Supported Note
Data backups are stored directly on the PolarDB distributed storage system. |
Supported Note
Data backup files are stored locally. |
|
|
PolarDB supports full restoration and database and table restoration. Both methods support restoring from a backup set or to a past point in time. The database and table restoration feature does not overwrite or delete existing databases and tables in the original cluster. It creates new databases and tables in the original cluster instead of writing data into the original ones. |
Supported |
Supported |
||
|
High Availability |
Single-zone high availability |
The multi-node deployment architecture ensures high availability for the cluster. When a system failure occurs, an automatic failover is performed between the read-write primary node and the read-only nodes. |
Supported |
Supported |
|
Supports creating multi-zone clusters. Compared to single-zone clusters, multi-zone clusters provide higher disaster recovery capabilities and can withstand data center-level failures. |
Supported |
Supported |
||
|
High Security |
Supports management of console accounts and database accounts. |
Supported |
Supported |
|
|
After you create a PolarDB for PostgreSQL database cluster, you must configure an IP address whitelist and create an initial account for the cluster. Only IP addresses added to the whitelist or ECS instances in the security group can access the cluster. |
Supported |
Supported |
||
|
To improve link security, you can enable Secure Sockets Layer (SSL) encryption and install an SSL CA certificate on the required application services. SSL encrypts network connections at the transport layer, which enhances the security and integrity of communication data but increases the response time of network connections. |
Supported |
Supported |
||
|
Transparent Data Encryption (TDE) performs real-time I/O encryption and decryption on data files. Data is encrypted before being written to disk and decrypted when read from disk into memory. TDE does not increase the size of data files. Developers can use the TDE feature without changing any applications. |
Supported |
Supported |
||
|
PolarDB for PostgreSQL provides an SQL throttling feature. This feature configures throttling rules based on connection addresses to prevent business impact from SQL statements caused by unusual traffic. |
Supported |
Supported |
||
|
Connection Management |
PolarDB supports transaction-level connection pooling. You can use transaction-level connection pooling as needed to help reduce the database load pressure caused by many connections. |
Supported |
Supported |
|
|
PolarDB provides three consistency levels: eventual consistency, session consistency, and global consistency. These levels meet your requirements for different scenarios. |
Supported |
Supported |
||
|
Plugin Management |
Plugins for PolarDB for PostgreSQL can extend database features. For example, they can implement heterogeneous data access, support similarity calculations, and enable full-text search. This allows for flexible adaptation to business needs, improving developer efficiency and system stability. |
Supported |
Supported |
|
|
GanosBase |
Provides integrated expression, storage, query, analysis, and rendering support for new types of spatio-temporal, multi-modal, and polymorphic data. It solves problems such as complex workflows, high barriers to entry, and low application efficiency in traditional spatio-temporal big data usage. It can be widely used in fields such as urban management, transportation and logistics, shared mobility, natural resources, aerospace, and IoT information. |
Supported |
Supported |
|
|
Cost-effectiveness |
PolarDB for PostgreSQL supports tiered storage for hot and cold data. It uses lower-cost storage media such as Object Storage Service (OSS) to store data in tiers. Transferring infrequently accessed and updated data to OSS can effectively reduce storage costs. |
Supported |
Support |
|
|
Monitoring and Optimization |
The PolarDB console provides rich performance monitoring metrics and second-level monitoring frequency. This helps you understand the running status of your cluster and quickly locate O&M issues with fine-grained monitoring data. |
Supported |
Supported |
|
|
PolarDB for PostgreSQL integrates some features of Database Autonomy Service (DAS). It supports features such as session management, real-time performance, storage analysis, and Performance Insight. This makes it easy for you to view database-related diagnostic and optimization results. |
Supported |
Supported |
||
|
Provides a slow SQL analysis feature that lets you view slow log trends and performance statistics. It also provides SQL suggestions and diagnostic analysis. |
Supported |
Support |
||
|
The SQL Explorer feature has been upgraded to SQL Explorer and Audit. Provided by Database Autonomy Service (DAS), SQL Explorer and Audit integrates features such as search, SQL exploration, security audit, and traffic playback and stress testing on top of full request logging and security auditing. This helps you better obtain specific information about SQL statements, troubleshoot various performance issues, and identify high-risk sources. |
Supported |
Supported |
||
|
PolarDB for AI |
Polar_AI is an AI extension for the cloud-native database PolarDB. It integrates advanced AI models and algorithms to build a bridge between the database and modern artificial intelligence technologies. This enables the database to perform tasks such as machine learning and natural language processing. |
Support |
Supported |
|
|
Data Migration & Synchronization |
PolarDB supports one-click migration from an ApsaraDB RDS database while retaining the original endpoint. |
Supported |
Supported |
|
|
PolarDB supports migrating self-managed databases to the cloud. |
Supported |
Supported |