Comparing Amazon Redshift Serverless to an Amazon Redshift provisioned data warehouse
For Amazon Redshift Serverless, some concepts and features are different than their corresponding feature for an Amazon Redshift provisioned data warehouse. For instance, one contrasting comparison is that Amazon Redshift Serverless doesn't have the concept of a cluster or node. The following table describes features and behavior in Amazon Redshift Serverless and explains how they differ from the equivalent feature in a provisioned data warehouse.
| Feature | Description | Serverless | Provisioned |
|---|---|---|---|
Workgroup and Namespace |
To isolate workloads and manage different resources in Amazon Redshift Serverless, you can create namespaces and workgroups in order to manage storage and compute resources separately. |
A namespace is a collection of database objects and users. A workgroup is a collection of compute resources. For more information, see Amazon Redshift Serverless to understand the design for Amazon Redshift Serverless. |
A provisioned cluster is a collection of compute nodes and a leader node, which you manage directly. For more information, see Amazon Redshift provisioned clusters. |
Node types |
When you work with Amazon Redshift Serverless, you don't choose node types or specify node count like you do with a provisioned Amazon Redshift cluster. |
Amazon Redshift Serverless automatically provisions and manages capacity for you. You can optionally specify base data warehouse capacity to select the right price/performance balance for your workloads. You can also specify maximum RPU hours to set cost controls to make sure that costs are predictable. For more information, see Understanding Amazon Redshift Serverless capacity. |
You build a cluster with node types that meet your cost and performance specifications. For more information, see Amazon Redshift provisioned clusters. |
Workload management and concurrency scaling |
Amazon Redshift can scale for periods of heavy load. Amazon Redshift Serverless also can scale to meet intermittent periods of high load. |
Amazon Redshift Serverless automatically manages resources efficiently and scales, based on workloads, within the thresholds of cost controls. For more information, see Billing for compute capacity. |
With a provisioned data warehouse, you enable concurrency scaling on your cluster to handle periods of heavy load. For more information, see Concurrency scaling. |
Port |
The port number that you use to connect. |
With Amazon Redshift Serverless, you can change to another port from the port range of 5431–5455 or 8191–8215. For more information, see Connecting to Amazon Redshift Serverless. |
With a provisioned data warehouse, you can choose any port to connect. |
Resizing |
Add or remove compute resources to perform well for the workload. |
Resizing is not applicable in Amazon Redshift Serverless. You can however change the base data warehouse RPU capacity, based on your price and performance requirements. For more information, see Understanding Amazon Redshift Serverless capacity. |
With a provisioned cluster, you perform a cluster resize to add nodes or remove nodes. For more information, see Overview of managing clusters in Amazon Redshift. |
Pausing and resuming |
You can pause a provisioned cluster when you don't have workloads to run, to save cost. |
With Amazon Redshift Serverless, you pay only when queries run, so there is no need to pause or resume. For more information, see Billing for compute capacity. |
You pause and resume a cluster manually, based on an assessment of your workload at various times. For more information, see Overview of managing clusters in Amazon Redshift. |
Querying external data with Spectrum queries |
You can query data in Amazon S3 buckets, in a variety of formats, such as JSON. |
Billing accrues when compute resources process workloads. Also, billing accrues when external Redshift Spectrum data is queried, like any other transaction. For more information, see Billing for compute capacity. |
With a provisioned data warehouse, Amazon Redshift Spectrum capacity exists on separate servers that are queried from the Amazon Redshift cluster. For more information, see Querying external data using Amazon Redshift Spectrum. |
Compute-resource billing |
How billing accrues for Amazon Redshift vs Amazon Redshift Serverless. |
With Amazon Redshift Serverless, you pay for the workloads you run, in RPU-hours on a per-second basis, with a 60-second minimum charge. This includes queries that access data in open file formats in Amazon S3. For more information, see Billing for compute capacity. |
With a provisioned cluster, billing occurs per second when the cluster isn't paused. |
Maintenance window |
How server maintenance works. |
With Amazon Redshift Serverless, there is no maintenance window. Updates are handled seamlessly. For more information, see What is Amazon Redshift Serverless? |
With a provisioned cluster, you specify a maintenance window when patching occurs. (Typically, you choose a recurring time when use is low.) |
Encryption |
You can enable database encryption. |
Amazon Redshift Serverless is always encrypted with AWS KMS, with AWS managed or customer managed keys. |
The data in a provisioned data warehouse can be encrypted with AWS KMS (with AWS managed or customer managed keys), or unencrypted. See Amazon Redshift database encryption. |
Storage billing |
How billing for storage works. |
For Amazon Redshift Serverless. The rate is calculated according to GB per month. See Billing for compute capacity. |
Storage is billed apart from compute resources for a provisioned cluster with RA3 nodes. |
User management |
How users are managed. |
For Amazon Redshift Serverless, users are IAM or Redshift users. For more information, see Identity and access management in Amazon Redshift Serverless. For more information about managing IAM identities, including best practices for IAM roles, see Identity and access management in Amazon Redshift. |
For a provisioned data warehouse, users are IAM or Redshift users. For more information, see Managing database security in the Amazon Redshift Database Developer Guide. For more information about managing IAM identities, including best practices for IAM roles, see Identity and access management in Amazon Redshift. |
JDBC and ODBC tools and compatibility |
How client connections work. |
Amazon Redshift Serverless is compatible with any JDBC or ODBC compliant tool or client application. For more information about drivers, see Configuring connections in the Amazon Redshift Management Guide. For information about connecting to Amazon Redshift Serverless, see Connecting to Redshift Serverless. |
Amazon Redshift provisioned is compatible with any JDBC or ODBC compliant tool or client application. For more information about drivers, see Configuring connections in the Amazon Redshift Management Guide. For information about connecting to clusters, see Connecting to an Amazon Redshift data warehouse using SQL client tools. |
Requirement for credentials on sign in |
How credentials are handled. |
For Amazon Redshift Serverless, you don't have to enter credentials in every instance. For more information, see Connecting to Amazon Redshift Serverless. |
Access to Amazon Redshift requires sign-in credentials from a user associated with an IAM role. The IAM role has specific permissions attached for a provisioned data warehouse. Once authenticated, the user can connect directly to the database, to the Redshift console, and to query editor v2. |
Data API |
You can access data from web services and other applications. |
Amazon Redshift Serverless supports the Amazon Redshift Data API. With Amazon Redshift Serverless, you
use the |
Amazon Redshift provisioned supports the Amazon Redshift Data API. With Amazon Redshift clusters, you
use the |
Snapshots |
Provides point-in-time recovery. |
Amazon Redshift Serverless supports snapshots and recovery points. For more information about snapshots and recovery points for a namespace, see Working with snapshots and recovery points. |
Provisioned clusters support snapshots. For more information, see Managing snapshots using the console. |
Data Sharing |
Provides the ability to share data between databases in the same account or in different accounts. |
Amazon Redshift Serverless supports all of the data sharing features that a provisioned data warehouse does. It also supports data sharing between Amazon Redshift Serverless and a provisioned data warehouse, tool, or client application. |
Provisioned clusters support cross database, cross account, cross-Region, and AWS Data Exchange data sharing. For more information, see Sharing data across clusters in Amazon Redshift. |
Tracks |
Provides a schedule for software updates. |
Amazon Redshift Serverless has no concept of a track. Versions and updates are handled by the service. For more information about the design of Amazon Redshift Serverless, see Working with snapshots and recovery points. |
Provisioned clusters support switching between current and trailing tracks. |
System tables and views |
Provides a way to monitor your resources and system metadata. |
Amazon Redshift Serverless supports new system tables and views. For more information about system tables, see Monitoring views. For information about how to migrate your queries from using the older provisioned system tables and views to the new views, see Migrating to SYS monitoring views. |
A provisioned data warehouse supports the existing set of system tables and views for monitoring and other tasks that require system metadata. |
Parameter groups |
This is a group of parameters that apply to all of the databases created in a cluster. These parameters configure database settings such as query timeout and date style. |
Amazon Redshift Serverless does not have the concept of a parameter group. |
Provisioned data warehouses support parameter groups. For more information about parameter groups for a provisioned cluster, see Amazon Redshift parameter groups. |
Query monitoring |
Provides a time-based view of queries run. |
Query monitoring in Amazon Redshift Serverless requires users to connect to the database to use system tables. Thus, query monitoring and system tables are in sync. Queries of system tables in Amazon Redshift Serverless use the database user mapped to the IAM user for using query monitoring. For more information about monitoring queries, see Monitoring queries and workloads with Amazon Redshift Serverless. |
Query monitoring in provisioned clusters does not show all data in system tables. |
Audit logging |
Provides information about connections and user activities in the database. |
With Amazon Redshift Serverless, CloudWatch is a destination for audit logs. Amazon S3 based audit log delivery is not supported for Amazon Redshift Serverless. For more information, see Audit logging for Amazon Redshift Serverless. |
For a provisioned cluster, Amazon S3-based audit log delivery has been the norm. Now, delivery of audit logs to CloudWatch is extended to cover provisioned data warehouses. |
Event notifications |
Amazon EventBridge is a serverless event bus service that you can use to connect your applications with event data from a variety of sources. |
Amazon Redshift Serverless uses Amazon EventBridge to manage event notifications to keep you up-to-date regarding changes in your data warehouse. For more information, see Amazon Redshift Serverless event notifications with Amazon EventBridge. |
For a provisioned cluster, you manage event notifications using the Amazon Redshift console to create event subscriptions. For more information, see Managing cluster event notifications . |
