Overview
Cloud Data Warehouse provides cloud-based ClickHouse hosting services that are user-friendly, adaptable, and reliable. Within minutes, users can create a data warehouse capable of handling massive real-time data queries and analysis, thus enhancing the efficiency of data value extraction.
Benefits
Superior Performance
Cloud Data Warehouse utilizes a distributed massively parallel processing (MPP) architecture, enabling query processing at significantly faster speeds compared to traditional data warehouses. This acceleration remains consistent even when dealing with terabytes of data per second per query.
Ease of Use
In just minutes, you can set up a ClickHouse analysis cluster directly from the console. With a range of features including OPS management, monitoring, and alerting, you are freed from the complexities of infrastructure management, allowing you to concentrate on extracting the full value of data analysis with comprehensive SQL statements.
Elastic Scalability
The Cloud Data Warehouse console streamlines and expedites cluster scaling and node configuration adjustments, offering dynamic support to accommodate rapid business expansion with superior scalability.
High Cost-Effectiveness
Cloud Data Warehouse empowers you to construct cost-effective managed ClickHouse clusters utilizing cloud-based resources. This encompasses harnessing ClickHouse’s 10x data compression algorithm, which significantly decreases disk usage and expenses compared to conventional data warehouses.
Security and Reliability
Your clusters are deployed independently within isolated VPCs to ensure secure data access. Additionally, the Cloud Data Warehouse fully supports high-availability clusters, enabling seamless service disaster recovery and failover mechanisms that are transparent to users.
Features
Advanced OPS
Cloud Hosting
Basic OPS
Ecological Integration
Permission Management: Control permissions at the database table level, alongside defining common and high-risk permission configuration policies.
Data Table Management: Monitor differences in table metadata and data distribution across nodes, including skew checks.
Hot/Cold Data Tiering: Implement cold data storage in COS buckets, configure hot/cold data tiering coefficients, adjust partitioning levels between hot/warm/cold data, and manage Time-To-Live (TTL) settings.
Backup and Restore: Perform metadata backup and clone non-system tables within clusters, as well as backup and restore data to local tables.
Query Management: Analyze and manage queries, including monitoring running queries, tracking historical slow queries, and accessing query details.
Dictionary Management: Associate and manage dictionary tables, including those sourced from external databases like MySQL and ClickHouse.
DW Studio: Handle connection management, visualize query results, utilize smart workspace prompts, apply keyword highlighting, and format SQL queries.
Metadata Management: Reconstruct nodes after scaling operations and conduct regular metadata backups.
- Lifecycle management: includes horizontal scaling, vertical configuration adjustments, and billing conversion for CK/ZK nodes.
- Cluster configuration management: handles parameter setup and management.
- Monitoring and alerting: options for purchasing and refunding basic (free) or advanced monitoring and alerting services on CK/ZK nodes.
- Log search: facilitates log collection and exception log searches across all nodes.
- Data Integration: Seamlessly input data from multiple sources including ClickHouse, MySQL, Oracle, DB2, PostgreSQL, CKafka, Hive, and HBase.
- Real-Time Writing: Utilize Oceanus for real-time processing linkage with ClickHouse, supporting INSERT, UPDATE, and DELETE operations to ensure data consistency.
- Cluster Migration: Facilitate cross-cloud data migration from self-hosted ClickHouse clusters to the Cloud Data Warehouse.
Scenarios
User Behavior Analysis
BI Analysis/Data Dashboard
A/B Testing Platform
Cloud Data Warehouse enables the collection of various data types, including clicks, operations, browsing, payments, and comments from websites, apps, and games, to message channels. This data is parsed, processed, and stored by a real-time computing platform, and then further analyzed by Cloud Data Warehouse across multiple dimensions. Cloud Data Warehouse excels in querying and responds in milliseconds for real-time data extraction, analysis, drilling, retention analysis, and funnel analysis. This significantly speeds up big data analysis and processing, offering robust support for targeted marketing and membership conversion.
Scientific exploration is inherently random and challenging to pre-model. Cloud Data Warehouse provides a solution for importing business data on a large scale, allowing you to build a real-time data analysis platform. With rapid query capabilities and flexible scaling, Cloud Data Warehouse significantly streamlines data exploration and enables real-time analysis of metrics such as PV, UV, revenue, and user groups. This allows for uninterrupted personalized analysis, empowering you to make well-informed business decisions at any time.
A/B testing employs data-driven methods for adaptable traffic segmentation. This allows for multiple versions of a product to be simultaneously available online, enabling the comparison of user behaviors across each version. Such insights aid in making informed decisions based on scientifically precise results.
The Cloud Data Warehouse excels in conducting custom analyses of petabytes of log data within seconds. With its high-performance storage and data aggregation capabilities, it emerges as the optimal solution for experiment analysis. By integrating both offline and real-time user behavior logs to compute event tracking data, it enhances the accuracy of experiment results and accelerates the experiment cycle and model validation process.
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