The document discusses ApsaraDB, a cloud database solution by Alibaba, highlighting its capabilities in addressing business data deployment challenges, including performance, security, and operational management. It outlines various database types supported, such as MySQL, PostgreSQL, and MongoDB, and features like automated management, high availability, and data security measures. Additionally, it provides examples of typical customers, illustrating ApsaraDB's effectiveness in real-world applications, such as improving processing times for large-scale financial computations.

1. Presenter: David Wang
Alibaba Cloud Product Specialist
Leveraging ApsaraDB to
Deploy Business Data
on the Cloud

2. Outline
ApsaraDB Introduction Countering Challenges Functional Solutions Typical Customers
Introduction to ApsaraDB

3. Business
Applications
Redis
Memcache
MySQL
SQL Server
PostgreSQL
MongoDB
PPAS (Oracle)
POLARDB
Hbase
HybridDB for MySQL(PetaData)
HybridDB for PG(GreenPlum)
Product Relationships
Cache Fast Storage Long-term Analysis Big
Covers over 70% of key online database engines

4. Product Relationships
ApsaraDB
RDS
MySQL
SQL Server
PostgreSQL
PPAS(Oracle)
NoSQL
Redis
MongoDB
Memcahce
Data
Warehousing
HBase
HTAP
ADS
Tools
DTS
DMS
HybridDB for MySQL(PetaData)
HybridDB for PostgreSQL(GreenPlum)

5. Product Features
High
Availability
SSDs used as storage, verifiable backup
restorability at any time
The first RCPIS Grade III
cloud database in China
Master-Slave backup nodes & disaster tolerance
solutions to ensure business continuity
Automated management & monitoring
Top database expert team to provide
customer support
Raft algorithm guaranteed consistency
Free migration of full or incremental
data without downtime

6. ApsaraDB Introduction Countering Challenges Functional Solutions Typical Customers

7. ApsaraDB Usage
Poor Database
Performance Weak O&M Platform
Sensitive Data
Difficulties Recruiting
DBAs
Current Issues

8. Poor Database Performance
Performance & Capacity
- 60 CPUs + 470 GB memory
(exclusive physical machines)
- 2TB SSD＋50000 IOPS
- 100,000–150,000 QPS
- No-downtime configuration changes
Source Code Improvements
- MySQLPostgreSQLRedisMongoDB
- Locks, transaction optimization, and
optimized master/slave syncing to improve
performance 3–5 times over

9. Sensitive Data
Security Features
VPC: Isolated network environments
IP Whitelist: Controlled client sources
SSL: Encrypted network traffic
TDE: Transparent data encryption
SQL audit tracking: Detailed access records

10. Weak O&M Platform
Automated O&M
• Fault self-recovery
• Backup self-verification
• High-frequency monitoring
• Webpage operations
• Comprehensive analysis for resources, SQL databases,
and engines
- CPU resources
- Memory resources
- Storage resources
- Connection count IOPS
- Statement consumption
summary and ranking
- Execution plan analysis
- Table structure analysis
- Database lock analysis
- Transaction optimization analysis
- Deadlock rollback

11. Difficulties Recruiting DBAs
Expert Services
• Implementation of data migration to the cloud
• Database emergency support
• Database health diagnostics
• Business escort service for high-traffic events
• Customized open-source database source code
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12. ApsaraDB Introduction Countering Challenges Functional Solutions Typical Customers

13. Functions List
Function ApsaraDB ECS User-created Database
Service availability
Master/Backup architecture ✔️ Hot standby ✖️
Local disaster tolerance ✔️ Multiple zones ✖️
Remote disaster tolerance ✔️ DR instances ✖️
Fault drills ✔️ Master/Backup switchover ✖️
Data reliability
Online storage redundancy ✔️ Local RAID ✔️ Ultra/SSD cloud disks
Offline long-term backup ✔️ Up to 730 days ✖️
Time point recovery ✔️ Instance clone ✖️
Data replication ✔️ Asynchronous/Semisynchronous ✖️
Data security
Network isolation ✔️ White list groups ✔️ ECS security groups
Audit logs ✔️ SQL audit/keyword filtering ✖️
Network encryption ✔️ SSL ✖️
Encrypted storage ✔️ TDE ✖️
Monitoring and alarms
Resource monitoring ✔️ CPU/MEM/DISK/IOPS ✔️
Engine monitoring ✔️ QPS/TPS/etc ✖️
Seconds-level monitoring ✔️ 300s/60s ✔️ 300s
Cloud Monitor alarms ✔️ Resource alarms/Availability alarms ✖️
Parameter management
Parameter templates ✔️ Almost 100 optional parameters ✖️
Change history ✔️ Change record tracing ✖️
Performance optimization
Overhead cost analysis ✔️ SQL consumption statistics ✖️
Optimization recommendations ✔️ Missing index analysis ✖️
All-in-one service
Data management ✔️ DMS visual user interface ✖️
Data synchronization ✔️ DTS online data migration/subscription ✖️

14. Disaster Tolerance Solution
East China
Zone A
Intranet
• Disaster tolerance within a data center: Two nodes in different racks
• Dual-data center local disaster tolerance: Log latency no longer than 3ms. Select "Multi-zone" during instance activation.
• Coming soon: Dual-data center, tri-copy local disaster tolerance
• Remote disaster tolerance: Log transmission delay of shorter than 1 second between two data centers located 300 km to
1000 km apart
Master
South China
Zone A
Leased
Line
M S
Master
Zone B
Provides 3 levels of high-availability (disaster tolerance) architectures for selection

15. Read/Write Splitting
Provides single-point "read scaling" capabilities
• 10 read-only nodes
• Independent connection address
• Adjustable configurations
Data Sync in
MillisecondsRead-only Requests
Loading
Read/Write
Service

16. Heterogeneous Data Storage
• Provides “hotspot data” capabilities
• Distributed memory cluster
• Up to 512 GB for a single instance
• Simple protocols (MemCache/Redis)
Hotspot Data
Persistent Data
Access
Common
Transactions

17. Data Storage Scaling
(For Relational Databases)
Distributed, low cost,
PB-level storage
• Designed for IoT data storage and log
data storage scenarios
• Provides 3–5 years' capacity planning
capabilities to enterprises
• 7–10x compression capabilities
(100 GB –> 15 GB)
• Improves Insert performance by 10x
• Over 70% compatible with MySQL
Application
Adaptation Costs HighNone
• 60 Core, 470 GB mem
• 2TB, 20000 IOPS
• Configuration change as desired
• 10 read-only nodes
• Independent connection address
• Adjustable configurations
• PetaData
• Simultaneous read/write scaling
• Data volumes from 8 TB to 1 PB
PolarDB, 100% compatible with MySQL, 100 TB

18. Data Storage Scaling
• Built-in distributed clusters
• Application integration with 0
code modification
• 512 GB max storage for a
single Redis instance
Memcache Redis MongoDB
• MongoDB Sharding, unlimited
memory and storage
(For NoSQL Databases)

19. Big Data Computing
Access to the Data Technology (DT) age:
renewed focus on how to make good use of d
ata
BI & Analytics
IoT & Real-time
Analytics
In-
house
Cloud Backup
Leased Line Access

20. ApsaraDB Introduction Countering Challenges Functional Solutions Typical Customers

21. Typical Customers
After Alipay launched its Yu'E Bao business,
Tianhong's accounting computation needs
surged.
Using RDS cluster instances for parallel
computing, the company's revenue accounting
time fell from 24 hours to 4 hours.
Alipay
Tianhong
Securities Yu’er Bao

22. Typical Customers
Chai Jing's documentary "Under the Dome"
released a pollution map app
The surge in users and traffic caused the app's
offline database to crash.
Using Alibaba Cloud’s Expert
Service, the database was
migrated to a read-only RDS
instance.
There, it was able to withstand
dozens of times more access
pressure.
Community Organization:
Pollution Map

23. Learn More About ApsaraDB for RDS
www.alibabacloud.com/tc (Chinese)
www.alibabacloud.com (English)