Overview

Cloud Data Warehouse offers easy-to-use, flexible, and stable ClickHouse hosting services in the cloud. A data warehouse can be created in minutes for massive real-time data query and analysis, improving the overall efficiency of data value mining.

Benefits
Superior Performance

Cloud Data Warehouse leverages distributed massively parallel processing (MPP) architecture, allowing you to process queries several times faster than traditional data warehouses, even up to terabytes of data per second per query.

Ease of Use

You can create a ClickHouse analysis cluster in minutes in the console. A diversity of features such as OPS management, monitoring, and alarming free you from underlying infrastructure management and let you focus on analyzing data value with complete SQL statements.

Elastic Scalability

The Cloud Data Warehouse console simplifies and accelerates cluster scaling and node configuration adjustment, providing dynamic support for rapid business growth with high scalability.

High Cost-Effectiveness

Cloud Data Warehouse enables you to build highly cost-effective managed ClickHouse clusters with devices in the cloud. This includes leveraging the 10x data compression algorithm of ClickHouse to efficiently reduce disk usage and costs compared with traditional data warehouses.

Security and Reliability

Your clusters are independently deployed in isolated VPCs for more secure data access. Moreover, Cloud Data Warehouse provides full support for high-availability clusters to implement service disaster recovery and failover that is imperceptible to users.

Features

Advanced OPS

Cloud Hosting

Basic OPS

Ecological Integration

Advanced OPS

  • Permission management: permission management at the database table level as well as common and high-risk permission configuration policies.
  • Data table management: differences between table metadata and data distribution (skew check) across nodes.
  • Hot/Cold data tiering: cold data storage in COS bucket, configurable hot/cold data tiering coefficients, swap of hot/warm/cold data partitioning levels, and TTL swap.
  • Backup and restore: metadata backup and cloning of non-system tables in clusters as well as data backup and restore to local tables.
  • Query management: query analysis and management (running queries, historical slow queries, and query details).
  • Dictionary management: association and management of dictionary tables, including those from external sources such as MySQL and ClickHouse.
  • DW Studio: connection management, table/views/dictionary tables, visualized query results, smart workspace prompts, keyword highlighting, and SQL formatting.
  • Metadata management: node reconstruction after scaling and regular metadata backup.

Cloud Hosting

Cloud Data Warehouse enables you to build a data warehouse at the terabyte or even petabyte scale in just a few minutes. With mature cluster management functionality, it reduces the heavy workload of cost management, cluster configuration adjustment, and parameter configuration in the console.

Basic OPS

  • Lifecycle management: horizontal scaling, vertical configuration adjustment, and billing conversion on CK/ZK nodes.
  • Cluster configuration management: parameter configuration and management.
  • Monitoring and alarming: purchase and refund of basic (free)/advanced monitoring and alarming on CK/ZK nodes.
  • Log search: log collection and exception log search on all nodes.

Ecological Integration

  • Data integration: data input from multiple sources such as ClickHouse, MySQL, Oracle, DB2, PostgreSQL, CKafka, Hive, and HBase.
  • Real-time writing: Oceanus real-time processing linkage for ClickHouse, with INSERT, UPDATE, and DELETE operations supported for writing to ensure data consistency.
  • Cluster migration: cross-cloud data migration from self-built ClickHouse clusters to Cloud Data Warehouse.
Features
  • Permission management: permission management at the database table level as well as common and high-risk permission configuration policies.
  • Data table management: differences between table metadata and data distribution (skew check) across nodes.
  • Hot/Cold data tiering: cold data storage in COS bucket, configurable hot/cold data tiering coefficients, swap of hot/warm/cold data partitioning levels, and TTL swap.
  • Backup and restore: metadata backup and cloning of non-system tables in clusters as well as data backup and restore to local tables.
  • Query management: query analysis and management (running queries, historical slow queries, and query details).
  • Dictionary management: association and management of dictionary tables, including those from external sources such as MySQL and ClickHouse.
  • DW Studio: connection management, table/views/dictionary tables, visualized query results, smart workspace prompts, keyword highlighting, and SQL formatting.
  • Metadata management: node reconstruction after scaling and regular metadata backup.

Cloud Data Warehouse enables you to build a data warehouse at the terabyte or even petabyte scale in just a few minutes. With mature cluster management functionality, it reduces the heavy workload of cost management, cluster configuration adjustment, and parameter configuration in the console.

  • Lifecycle management: horizontal scaling, vertical configuration adjustment, and billing conversion on CK/ZK nodes.
  • Cluster configuration management: parameter configuration and management.
  • Monitoring and alarming: purchase and refund of basic (free)/advanced monitoring and alarming on CK/ZK nodes.
  • Log search: log collection and exception log search on all nodes.
  • Data integration: data input from multiple sources such as ClickHouse, MySQL, Oracle, DB2, PostgreSQL, CKafka, Hive, and HBase.
  • Real-time writing: Oceanus real-time processing linkage for ClickHouse, with INSERT, UPDATE, and DELETE operations supported for writing to ensure data consistency.
  • Cluster migration: cross-cloud data migration from self-built ClickHouse clusters to Cloud Data Warehouse.
Scenarios

Cloud Data Warehouse allows you to collect data such as clicks, operations, browsing, payments, and comments on websites, apps, and games to message channels. The data is parsed, processed, and stored by a real-time computing platform and further analyzed by Cloud Data Warehouse in multiple dimensions. Cloud Data Warehouse excels in query and responds in milliseconds in terms of real-time data extraction/analysis/drilling, retention analysis, and funnel analysis. This greatly accelerates big data analysis and processing, providing strong support for targeted marketing and membership conversion.

Scientific exploration is random and thus difficult to pre-model. Cloud Data Warehouse offers you a way to import business data at a large scale and construct a real-time data analysis platform. With faster query and flexible scaling, Cloud Data Warehouse greatly simplifies data exploration and enables real-time analysis of PV, UV, revenue, user group, and other metrics, allowing you to perform personalized analysis at any time without interruption and make informed business decisions.

A/B testing is data-driven for flexible traffic slicing. Different versions of a product can be online at the same time, and user behaviors on each version can be compared, allowing you to make better decisions using the most scientific and accurate results possible.

Cloud Data Warehouse can perform custom analysis of petabytes of log data in seconds, and features high-performance storage and data aggregation functions, making it the best choice for experiment analysis. It integrates both offline and real-time user behavior logs to compute event tracking data, makes experiment results more accurate, and speeds up your experiment cycle and model validation.

Pricing

Cloud Data Warehouse is pay-as-you-go. Fees are charged hourly, and you only pay for what you use. When you create a Cloud Data Warehouse cluster, the fees for two billing cycles will be frozen in your Tencent Cloud account. If your account has a sufficient balance, the remaining amount will be refunded when the cluster is terminated. For more information, see Pricing.