PolarDB for PostgreSQL is available in Enterprise Edition and Standard Edition, which offer different features. This topic compares the two editions across 13 categories: Cluster management, Elastic management, High performance, Backup and restoration, High availability, High security, Connection management, Extension management, GanosBase, Cost-effectiveness, Monitoring and optimization, PolarDB for AI, and Data migration and synchronization. This comparison helps you select the edition that best suits your needs.
Feature comparison
The PolarDB for PostgreSQL Enterprise Edition and Standard Edition share a highly consistent core architecture and main features. This means you receive the core benefits of PolarDB regardless of the edition you choose. The performance differences between the two editions are mainly because of different hardware and software at the compute and storage layers. At the compute layer, the compute nodes of Enterprise Edition use physical machines without virtualization overhead, while Standard Edition uses ECS instances. At the storage layer, the performance varies based on the backend storage. For more information about the maximum queries per second (QPS) in different scenarios for clusters with the same specifications but different backend storage, see Performance comparison. The following table describes the feature differences between the two editions.
Feature availability depends on not only the product edition but also other prerequisites. For example, serverless clusters, which are clusters with the billing method set to Serverless, support only PostgreSQL 14. For more information about the prerequisites for each feature, see the specific feature description.
Category | Feature | Description | Enterprise Edition | Standard Edition |
Cluster management | x86 architecture | The x86 architecture is equipped with Intel processors and a high-performance network. This configuration comprehensively improves overall performance and stability to meet the requirements of enterprise applications for high business stability and computing performance. | Supported | Supported |
Yitian ARM architecture | The ARM architecture uses Alibaba Cloud's proprietary Yitian 710 processor chips and 25 GE smart high-speed network interface cards to provide 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. A cluster can also contain only one primary node. Multiple database nodes form the database engine layer. The primary node processes read and write requests. The read-only nodes process only read requests. An active-active failover is used between the primary node and read-only nodes to provide high availability for the database. | 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 released 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 parameters and node parameters in the console. | Supported | Supported | ||
A PolarDB cluster architecture consists of three layers: the database proxy (Proxy), the database kernel (DB), and the distributed storage (Store). You can upgrade the Proxy or the kernel separately, or upgrade them together. | Supported | Supported | ||
PolarDB for PostgreSQL provides a network channel management feature. You can use network channels to access data across databases in a flexible and convenient manner using methods such as foreign tables based on foreign data wrappers (FDWs) and dblink. | Supported | Supported | ||
Elastic management | After you create a PolarDB cluster, you can manually add read-only nodes of desired specifications or remove unneeded read-only nodes as needed. | Supported | Support | |
PolarDB clusters support online specification changes without the need to lock the database. It supports three-dimensional scaling capabilities. Specification changes take effect in minutes. The capabilities are vertical scaling of computing power, horizontal scaling of computing power, and horizontal scaling of storage space. | Supported | Supported | ||
Serverless is a dynamic elastic scaling capability of the cloud-native database PolarDB. Nodes in a cluster can elastically scale within seconds to handle sudden workload surges without affecting your business. During off-peak hours, the mechanism can automatically scale in resources to reduce costs. This is implemented as a cluster whose billing method is set to Serverless. | Not supported | Supported | ||
Serverless is a dynamic elastic scaling capability of the cloud-native database PolarDB. Nodes in a cluster can elastically scale within seconds to handle sudden workload surges without affecting your business. During off-peak hours, the mechanism can automatically scale in resources to reduce costs. This is implemented by manually enabling the serverless feature for clusters that have a subscription or pay-as-you-go billing method. | Supported | Not supported | ||
High performance | The and IMCI complement the native PostgreSQL execution engine. This synergy allows PolarDB to retain high-performance transaction processing capabilities and significantly improve the performance of complex queries. | Supported | Supported | |
Elastic Parallel Query (ePQ) provides guarantees for cross-node parallel execution, elastic computing, and elastic scaling. This gives PolarDB for PostgreSQL initial hybrid transactional and analytical processing (HTAP) capabilities. | Supported | Supported | ||
Supports multiple SQL query optimization methods, such as correlated subquery pull-up, plan freezing, cost-based query transformation, OR clause to UNION ALL conversion, and sublink pushdown. | Supported | Supported | ||
PolarDB partitioned tables are fully compatible with the syntax and features of native PostgreSQL. Compared with native PostgreSQL, PolarDB enhances performance and supports a rich set of partition types and combinations, allowing you to use partitioned tables more easily, simply, and efficiently. | Supported | Supported | ||
Provides a multitenant resource configuration feature to limit the amount of resources used by one or more processes and implement tenant-level resource limits. | Supported | Supported | ||
To reduce the frequency of file system calls, PolarDB for PostgreSQL implements a cache for the number of table file blocks (Relation Size Cache, RSC) at the storage management layer. It caches the number of blocks of a table in shared memory and updates the cached value in shared memory when the number of blocks changes. Queries for the number of table file blocks preferentially use the cache. This reduces the number of requests to the file system and accelerates SQL execution. | Supported | Supported | ||
PolarDB for PostgreSQL lets you configure a maintenance window during off-peak hours. It uses idle hardware resources during off-peak hours for active and full garbage collection. This reduces the frequency of automatic cleanup 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. In addition, a more efficient Plan Cache mechanism reduces the overhead of generating execution plans, thus improving performance. | Supported | Supported | ||
The global metadata cache (Global Cache) is a collective term for metadata caches in the shared memory of PolarDB for PostgreSQL that are shared by all processes. The Global Cache allows all processes to share the same cache entry, which improves memory utilization efficiency and reduces the risk of OOM errors. | Supported | Supported | ||
Backup and restoration | PolarDB supports data backups and redo log backups. A data backup is a full backup that creates a backup set of all cluster data at a specific point in time. A redo log backup is an incremental backup that records data changes after a full backup is created. You can use a full data backup and the subsequent redo log backups to restore a PolarDB cluster or specific databases and tables to any point in time. | Supported Note Data backups are directly stored 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 restoration from a backup set or to a point in time. The database and table restoration feature does not overwrite or delete existing databases or tables in the original cluster. Instead of writing data into the original databases or tables, this feature creates new databases and tables in the original cluster. | Supported | Supported | ||
High availability | Single-zone high availability | The multi-node architecture can be used to ensure high availability of the cluster. When a system failure occurs, an automatic failover is performed between the read-write primary node and a read-only node. | Supported | Supported |
Supports the creation of multi-zone clusters. Compared with single-zone clusters, multi-zone clusters have 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 also need to set an IP address whitelist for the cluster and create an initial account. 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 can improve the security and integrity of communication data, but also increases the network connection response time. | Supported | Supported | ||
Transparent Data Encryption (TDE) performs real-time I/O encryption and decryption on data files. Data is encrypted before it is written to disk and decrypted when it is 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. The SQL throttling feature configures throttling rules based on connection addresses to prevent SQL statements with unusual traffic from affecting your business. | Supported | Supported | ||
PolarDB for PostgreSQL provides the confidential database feature. Data is encrypted on the client side before it is sent to the database management system. The plaintext data is not visible to the database server. This provides strong data security with end-to-end encryption. | Supported | Supported | ||
Connection management | PolarDB supports transaction-level connection pooling. You can use transaction-level connection pooling based on your business needs to help reduce the database load caused by many connections. | Supported | Supported | |
PolarDB provides three consistency levels: eventual consistency, session consistency, and global consistency. These levels meet your consistency requirements in different scenarios. | Supported | Supported | ||
Extension management | PolarDB for PostgreSQL extensions can expand database functionality, such as implementing heterogeneous data access, supporting similarity calculations, and implementing full-text search. They can flexibly adapt to business needs and improve development efficiency and system stability. | Supported | Supported | |
GanosBase | Provides integrated expression, storage, query, analysis, and rendering support for new spatio-temporal multi-modal and polymorphic data. It solves problems such as complex processes, high barriers to entry, and low application efficiency in the use of spatio-temporal big data. It can be widely used in fields such as urban management, transportation and logistics, shared travel, natural resources, aerospace, and IoT information. | Supported | Supported | |
Cost-effectiveness | PolarDB for PostgreSQL supports the tiered storage feature for hot and cold data. It uses lower-cost storage media such as OSS to store hot and cold data in tiers. Transferring data with low access and update frequencies to OSS can effectively reduce storage costs. | Supported | Supported | |
Monitoring and optimization | The PolarDB console provides rich performance monitoring items and second-level monitoring frequency. This lets you understand the running status of your cluster and quickly locate O&M problems through fine-grained monitoring data. | Supported | Supported | |
PolarDB for PostgreSQL integrates some features of DAS and supports features such as Session Manager, real-time performance, storage analysis, and Performance Insight. This makes it convenient 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 statistics, and provides SQL suggestions and diagnostic analysis. | Supported | Supported | ||
The SQL Explorer feature has been upgraded to SQL Explorer and Audit. SQL Explorer and Audit is provided by Database Autonomy Service (DAS). Based on full request and security audit, it integrates features such as search, SQL Explorer, security audit, traffic playback, and stress testing. 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 of 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 allows the database to perform tasks such as machine learning and natural language processing. | Supported | Supported | |
Data migration & synchronization | PolarDB supports one-click migration from an RDS database, keeping the original endpoint. | Supported | Supported | |
PolarDB supports the migration of self-managed databases to the cloud. | Supported | Supported |