Overview

ApsaraDB for ClickHouse is a distributed column-oriented database service that provides real-time analysis. ApsaraDB for ClickHouse is high-performance and easy to use. ApsaraDB for ClickHouse meets various enterprise requirements. It is widely used in traffic analysis, marketing analysis, behavior analysis, crowd division, customer profiles, agile BI, data marts, network monitoring, distributed services, and link monitoring.

Benefits

Lower Cost and Better Performance Supports efficient SIMD instruction sets and a vectored execution engine. Improves query performance over 100 to 1000 times compared with traditional databases. Supports column-level high compression rate. Enterprise-Level Management Supports balancing and scaling during data redistribution, multi-tenant resource isolation, online database management, development task orchestration, and comprehensive data integration. Ease of Use Allows you to configure clusters, replicas, parameters, network security settings, and O&M systems with ease. Comprehensive O&M and Technical Support Provides monitoring and diagnosis systems for disks, CPU, memory, IOPS, database connections, read and write volume, TPS, ZooKeeper, and slow SQL queries. Provides technical support in real-time.

Features

Real-Time Analysis Based on Data Lakehouse Architecture

Provides compatible and open source services, optimized kernel, and professional technical support Tiered Hot and Cold Data Storage Supports data management based on hot storage usage and TTL, and automatic data movement based on specified policies. This reduces storage costs. Integration with OSS and MaxCompute Supports data imports from OSS and MaxCompute external tables and analyzes data based on the Data Lake architecture at low costs Resource Queue Supports creating multiple resource queues and binding users to the queues. Allows you to isolate resources based on users and define query priorities. Supports dynamic resource optimization of multiple queues

Comprehensive and Efficient Data Integration

Supports data imports from multiple sources to build a real-time data warehouse Real-Time Computing Services Supports real-time data writing from Flink, Spark, and Kafka Big Data Services Supports data synchronization from big data services, such as DataWorks and Data Management, and Directed Acyclic Graph (DAG)-based task scheduling Database Services Supports synchronizing database data using MaterializeMySQL, MySQL external tables, DataWorks, and Data Transmission Service

Easy-to-Use and Cloud-Native Features

Provides comprehensive O&M features to reduce costs Auto Scaling Supports cluster auto scaling to ensure balanced data distribution Monitoring Alert Provides monitoring and diagnosis systems for disks, CPU, memory, IOPS, database connections, read and write volume, TPS, ZooKeeper, and slow SQL queries. Provides technical support in real-time Online Database Management Supports online account management, network management, cluster parameter configuration, slow query management, and data dictionary management