MySQL Cluster is a database that provides high scalability, 99.999% availability, and real-time performance. It uses an auto-sharding and multi-master architecture that is ACID compliant. MySQL Cluster has a shared-nothing architecture with no single point of failure and self-healing capabilities.

1. MySQL Cluster
Web Scalability, 99.999% Availability
Andrew Morgan
@andrewmorgan
www.clusterdb.com

2. Safe Harbour Statement
The following is intended to outline our general product direction. It is
intended for information purposes only, and may not be incorporated into any
contract.
It is not a commitment to deliver any material, code, or functionality, and
should not be relied upon in making purchasing decisions. The development,
release, and timing of any features or functionality described for Oracle’s
products remains at the sole discretion of Oracle.
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3. MySQL Cluster: Overview
HIGH SCALE, • Auto-Sharding, Multi-Master
READS + WRITES • ACID Compliant, OLTP + Real-Time Analytics
99.999% • Shared nothing, no Single Point of Failure
AVAILABILITY • Self Healing + On-Line Operations
• In-Memory Optimization + Disk-Data
REAL-TIME
• Predictable Low-Latency, Bounded Access Time
• Key/Value + Complex, Relational Queries
SQL + NoSQL
• SQL + Memcached + JavaScript + Java + JPA + HTTP/REST & C++
• Open Source + Commercial Editions
LOW TCO
• Commodity hardware + Management, Monitoring Tools
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4. Who’s Using MySQL Cluster?
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5. MySQL Cluster Architecture
Clients
Application Layer
Management
Data Layer
MySQL Cluster Data Nodes
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6. MySQL Cluster Architecture
On-Line Scaling
Clients
Application Layer
Management
Management
Data Layer
MySQL Cluster Data Nodes
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7. http://clusterdb.com/u/pi
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8. MySQL Cluster Architecture
No Single Point of Failure
Clients
Application Layer
Management
Management
MySQL Cluster Data Nodes
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9. Automatic Data Partitioning
Table T1 Data Node 1
Px Partition
P1
Data Node 2
P2
P3 Data Node 3
P4
Data Node 4
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10. Automatic Data Partitioning
Table T1 Data Node 1
F1
Px Partition
P1
Data Node 2
P2
P3 Data Node 3
P4
Fx Primary Fragment Data Node 4
Fx Secondary Fragment
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11. Automatic Data Partitioning
Table T1 Data Node 1
F1
Px Partition
P1
Data Node 2
P2 F1
P3 Data Node 3
P4
Fx Primary Fragment Data Node 4
Fx Secondary Fragment
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12. Automatic Data Partitioning
Table T1 Data Node 1
F1
Px Partition
P1
Data Node 2
P2 F3 F1
P3 Data Node 3
P4
Fx Primary Fragment Data Node 4
Fx Secondary Fragment
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13. Automatic Data Partitioning
Table T1 Data Node 1
F1 F3
Px Partition
P1
Data Node 2
P2 F3 F1
P3 Data Node 3
P4
Fx Primary Fragment Data Node 4
Fx Secondary Fragment
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14. Automatic Data Partitioning
Table T1 Data Node 1
F1 F3
Px Partition
P1
Data Node 2
P2 F3 F1
P3 Data Node 3
F2 F4
P4
Fx Primary Fragment Data Node 4
F4 F2
Fx Secondary Fragment
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15. Automatic Data Partitioning
Table T1 Data Node 1
F1 F3
Px Partition
P1 Node Group 1
Data Node 2
P2 F3 F1
P3 Data Node 3
F2 F4
P4
Node Group 2
Fx Primary Fragment Data Node 4
F4 F2
Fx Secondary Fragment
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16. Automatic Data Partitioning
Table T1 Data Node 1
F1 F3
Px Partition
P1 Node Group 1
Data Node 2
P2 F3 F1
P3 Data Node 3
F2 F4
P4
Node Group 2
Fx Primary Fragment Data Node 4
F4 F2
Fx Secondary Fragment
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17. On-line Scheduled Maintenance
Scale Backup
Evolve Upgrade
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18. Multi-Data Center Availability
Geographic Replication
 DR and Data Locality
 Replicate complete clusters
across data centers
– Fully active/active
– No passive resources
Geographic
Replication  Split individual clusters across
data centers
– Synchronous replication &
auto-failover between sites
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19. 1.2 Billion UPDATEs per Minute
25
Millions of UPDATEs per
20
Second
15
10
5
0
2 4 6 8 10 12 14 16 18 20 22 24 26 28 30
MySQL Cluster Data Nodes
 NoSQL C++ API, flexaSynch benchmark
 30 x Intel E5-2600 Intel Servers, 2 socket, 64GB
 ACID Transactions, with Synchronous Replication
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20. Real-World Test Case
Query Execution Time Seconds
100
90
80
70
60
87.23 seconds 70x
50
40
Faster
30
20
10
0 1.26 seconds
MySQL Cluster 7.1 MySQL Cluster 7.2
 Web-Based Content Management System
– JOINs 11-tables, 33.5k rows
– Returns 2k rows, 19 columns per row
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21. MySQL Cluster 7.3 EA: Node.js NoSQL API
 Native JavaScript access to MySQL Cluster
– End-to-End JavaScript: browser to the app and
database
– Storing and retrieving JavaScript objects directly
in MySQL Cluster
– Eliminate SQL transformation
 Implemented as a module for node.js
– Integrates full Cluster API library within the web
app
 Couple high performance, distributed apps, with
high performance distributed database
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22. MySQL Cluster 7.3 DMR1: Foreign Keys
 Brings MySQL Cluster to a broader range of workloads
– Packaged apps, custom projects
 Adds powerful functionality while reducing complexity
– App logic & data model
 Enabled by default
 Enforced for SQL
& NoSQL APIs
 On-line add and drop
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23. MySQL Cluster 7.2 and 7.3: Auto-Installer
Early Access Feature
 Best practices New!
 Fast configuration
 Workload optimized
Specify Auto-
Workload Discover
Define
Deploy Topology
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24. When to Consider MySQL Cluster
 Scalability demands
 Sharding for write performance?
 Latency demands
 Cost of each second?
 Uptime requirements
 Cost per minute of downtime?
 Failure versus maintenance?
 Application agility
 Developer languages and frameworks?
 SQL or NoSQL?
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25. Next Steps
Learn More
• www.mysql.com/cluster
• Authentic MySQL Curriculum:
http://oracle.com/education/mysql
Try it Out
• dev.mysql.com/cluster
• labs.mysql.com
• github.com/mysql/mysql-js
Let us know what you think
• clusterdb.com
• @clusterdb
• forums.mysql.com/list.php?25
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