Recommended Specs
15% OFF
Single-Replica Edition Single-Replica, Low Cost, and High Performance
A High-Performance Cloud-Native ClickHouse Service
Scenarios
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Analyzes more than 100 million log records
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Solves the write bottlenecks and stability issues of open-source Elasticsearch
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Supports user selection, real-time marketing, behavior analysis, and customer profiles
Analyzes more than 100 million log records
Specs
CPU 8 Cores or Up | 2 Nodes or Up | Single Replica
15% OFF
High-Availability Edition Double-Replica, DR Support, and High Availability
A High-Performance Cloud-Native ClickHouse Service
Scenarios
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Analyzes more than 100 million log records
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Solves the write bottlenecks and stability issues of open-source Elasticsearch
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Supports vertical and horizontal scaling of nodes
Specs
CPU 8 Cores or Up | 2 Nodes or Up | Double Replica
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
Typical Scenario
Quantitative Backtesting Analysis Based on Massive Historical Market Data
Financial companies engaged in quantitative trading typically use quantitative trading strategies and algorithms for investment. High-quality algorithms and high-quality quantitative backtesting are crucial for business profitability. Therefore, quantitative traders usually use the latest trading algorithms to test and review historical time-series data to determine profitability, a process known as backtesting. The complexity of the backtest model determines the number of parameters provided, such as initial capital, risk capital (%), portfolio size, commissions, average bid-ask spread, and benchmarks (e.g., S&P 500 index), helping traders evaluate the effectiveness of the latest trading strategies. Additionally, traders use current algorithms to backtest funds based on real-time trading conditions, track volatility, and predict future returns.
Solution Advantages
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Efficient Real-Time Analysis Performance
Wide table query performance of ApsaraDB for ClickHouse is about 900 times that of MySQL and 10 times that of ElasticSearch.
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Flexibility
MPP architecture of ApsaraDB for ClickHouse provides 50-200MB/s data writing capability per node, with linear scalability by adding nodes.
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Rich Functions
ApsaraDB for ClickHouse offers 150+ built-in functions for high-precision calculations with time-series data using time window functions, facilitating time-series data aggregation analysis.
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Low Cost
ApsaraDB for ClickHouse features cold-hot data tiered storage capability, allowing data archiving to low-cost storage, reducing storage costs by over 85%.
Recommendations
Customer Profile Analysis
Performs multi-dimensional analysis on user behaviors based on logs. Supports real-time business monitoring and real-time operations using screens
The Benefits of Our Solution
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Efficient Analysis
Provides efficient analysis capabilities. Queries for 100 billion log entries are completed within 30 seconds. 95% of the queries for 100 million log entries are completed within 5 seconds.
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Comprehensive Data Integration
Supports data imports from multiple big data services
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Efficient Writing
Provides high throughput and supports writing 10 billion log entries per hour during peak periods
Recommendations
User Selection and Precision Marketing
Analyzes historical data and cleans real-time user behavior data. Allows you to select required users for marketing based on the historical tags and real-time tags to increase daily active users (DAU).
The Benefits of Our Solution
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Efficient Analysis
Improves aggregation analysis performance 5 to 10 times over compared to traditional log analysis solutions. Queries for 100 million log entries are completed within milliseconds.
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Efficient and Stable Writing
Prevents OOM problems when writing a large amount of log data compared with Elasticsearch. Provides a write speed of 50 to 200 MB/s
Recommendations
Advertising Evaluation and User Profiles
Performs multi-dimensional analysis on a large amount of user data, identifies users for advertising, and evaluates advertising costs. Creates user profiles, evaluates advertising accuracy, and estimates expected profits.
The Benefits of Our Solution
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Efficient Analysis
Performs online analysis to identify users for advertising. Queries for 100 million data records in wide tables are completed within seconds.
