Editions
Databend Cloud comes in three editions: Personal, Business, and Dedicated, that you can choose from to serve a wide range of needs and ensure optimal performance for different use cases.
For a quick overview of these editions, see https://www.databend.com/databend-cloud. For the pricing information, see Pricing & Billing. For the detailed feature list among these editions, see Feature Lists.
Feature Lists
The following are feature lists of Databend Cloud among editions:
Release Management
| Features | Personal | Business | Dedicated |
|---|---|---|---|
| Early access to weekly new releases, which can be used for additional testing/validation before each release is deployed to your production accounts. | ✓ | ✓ |
Security & Governance
| Features | Personal | Business | Dedicated |
|---|---|---|---|
| SOC 2 Type II certification. | ✓ | ✓ | ✓ |
| GDPR | ✓ | ✓ | ✓ |
| Automatic encryption of all data. | ✓ | ✓ | ✓ |
| Object-level access control. | ✓ | ✓ | ✓ |
| Standard Time Travel (up to 1 day) for accessing/restoring modified and deleted data. | ✓ | ✓ | ✓ |
| Disaster recovery of modified/deleted data (for 7 days beyond Time Travel) through Fail-safe. | ✓ | ✓ | ✓ |
| Extended Time Travel. | 90 days | 90 days | |
| Column-level Security to apply masking policies to columns in tables or views. | ✓ | ✓ | ✓ |
| Audit the user access history through the Account Usage ACCESS_HISTORY view. | ✓ | ✓ | ✓ |
| Support for private connectivity to the Databend Cloud service using AWS PrivateLink. | ✓ | ✓ | |
| Dedicated metadata store and pool of compute resources (used in virtual warehouses). | ✓ |
Compute Resource
| Features | Personal | Business | Dedicated |
|---|---|---|---|
| Virtual warehouses, separate compute clusters for isolating query and data loading workloads. | ✓ | ✓ | ✓ |
| Multi-cluster scaling | ✓ | ✓ | |
| Resource monitors for monitoring virtual warehouse credit usage. | ✓ | ✓ | ✓ |
SQL Support
| Features | Personal | Business | Dedicated |
|---|---|---|---|
| Standard SQL, including most DDL and DML defined in SQL:1999. | ✓ | ✓ | ✓ |
| Advanced DML such as multi-table INSERT, MERGE, and multi-merge. | ✓ | ✓ | ✓ |
| Broad support for standard data types. | ✓ | ✓ | ✓ |
| Native support for semi-structured data (JSON, ORC, Parquet). | ✓ | ✓ | ✓ |
| Native support for geospatial data. | ✓ | ✓ | ✓ |
| Native support for unstructured data. | ✓ | ✓ | ✓ |
| Collation rules for string/text data in table columns. | ✓ | ✓ | ✓ |
| Multi-statement transactions. | ✓ | ✓ | ✓ |
| User-defined functions (UDFs) with support for JavaScript, Python, and WebAssembly. | ✓ | ✓ | |
| External functions for extending Databend Cloud to other development platforms. | ✓ | ✓ | ✓ |
| Amazon API Gateway private endpoints for external functions. | ✓ | ✓ | ✓ |
| External tables for referencing data in a cloud storage data lake. | ✓ | ✓ | ✓ |
| Support for clustering data in very large tables to improve query performance, with automatic maintenance of clustering. | ✓ | ✓ | ✓ |
| Search optimization for point lookup queries, with automatic maintenance. | ✓ | ✓ | ✓ |
| Materialized views, with automatic maintenance of results. | ✓ | ✓ | ✓ |
| Iceberg tables for referencing data in a cloud storage data lake. | ✓ | ✓ | ✓ |
| Schema detection for automatically detecting the schema in a set of staged semi-structured data files and retrieving the column definitions. | ✓ | ✓ | ✓ |
| Schema evolution for automatically evolving tables to support the structure of new data received from the data sources. | ✓ | ✓ | ✓ |
| Support for creating table with external location. | ✓ | ✓ | ✓ |
| Supports for ATTACH TABLE. | ✓ | ✓ | ✓ |
Interfaces & Tools
| Features | Personal | Business | Dedicated |
|---|---|---|---|
| The next-generation SQL worksheet for advanced query development, data analysis, and visualization. | ✓ | ✓ | ✓ |
| BendSQL, a command line client for building/testing queries, loading/unloading bulk data, and automating DDL operations. | ✓ | ✓ | ✓ |
| Programmatic interfaces for Rust, Python, Java, Node.js, .js, PHP, and Go. | ✓ | ✓ | ✓ |
| Native support for JDBC. | ✓ | ✓ | ✓ |
| Extensive ecosystem for connecting to ETL, BI, and other third-party vendors and technologies. | ✓ | ✓ | ✓ |
Data Import & Export
| Features | Personal | Business | Dedicated |
|---|---|---|---|
| Bulk loading from delimited flat files (CSV, TSV, etc.) and semi-structured data files (JSON, ORC, Parquet). | ✓ | ✓ | ✓ |
| Bulk unloading to delimited flat files and JSON files. | ✓ | ✓ | ✓ |
| Continuous micro-batch loading. | ✓ | ✓ | ✓ |
| Streaming for low-latency loading of streaming data. | ✓ | ✓ | ✓ |
| Databend Cloud Connector for Kafka for loading data from Apache Kafka topics. | ✓ | ✓ | ✓ |
Data Pipelines
| Features | Personal | Business | Dedicated |
|---|---|---|---|
| Streams for tracking table changes. | ✓ | ✓ | ✓ |
| Tasks for scheduling the execution of SQL statements, often in conjunction with table streams. | ✓ | ✓ | ✓ |
Customer Support
| Features | Personal | Business | Dedicated |
|---|---|---|---|
| Logging and tracking support tickets. | ✓ | ✓ | ✓ |
| 4/7 coverage and 1-hour response window for Severity 1 issues. | ✓ | ✓ | ✓ |
| Response to non-severity-1 issues in hours. | 8h | 4h | 1h |