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Enterprise Strategy Group | Getting to the bigger truth.™
© 2016 by The Enterprise Strategy Group, Inc.
Mike Leone, Senior ESG Lab Analyst
ESG Lab WebinarValidating ClustrixDB Performance in AWS
About Enterprise Strategy Group• ESG is an IT analyst, research, and strategy company.• Our firm was founded in 1999 with headquarters in Milford, MA / an analyst and client
relations presence in Silicon Valley, CA.• ESG conducts research with and for IT vendors, IT professionals, business professionals,
and channel partners.• We maintain ongoing analyst coverage in cloud computing, networking, storage, data
protection, cybersecurity, data management and analytics, application development and deployment, enterprise mobility, and channels.
• Capabilities include: Analyst services, market research, technical and economic validation, consulting, and custom content.• Mike Leone is a Senior ESG Lab Analyst with coverage across the entire IT industry.
• Provide in-depth testing and analysis of IT technology and products, using methods that simulate or recreate real-world environments.
• Extensive background in performance modeling, testing, and analysis.
© 2016 by The Enterprise Strategy Group, Inc.
Goals of this Webinar
Cloud Usage Trends and ChallengesWhat are the benefits of the cloud?How many people use it?What challenges exist when moving a traditional RDBMS to the cloud?Product Overview: ClustrixDBWhat is it? How is it different? How does it work?ESG Lab Performance ValidationGoals of the validation – comparing ClustrixDB performanceConfiguration, methodology, workload, etc.Performance analysis
– Single instance database comparison– ClustrixDB scale-out performance
ClustrixDB Performance TestingAdditional performance test comparisons and results
© 2016 by The Enterprise Strategy Group, Inc.
Benefits of the Cloud
Flexibility
Reliability
Cost-savings
Accessibility Manageability
© 2016 by The Enterprise Strategy Group, Inc.
Public Cloud Usage Trends
Platform-as-a-service (PaaS)
Infrastructure-as-a-service (IaaS)
Software-as-a-service (SaaS)
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
33%
38%
65%
10%
13%
24%
22%
17%
16%
15%
9%
15%
11%
7%
3%
1%
1%
Please indicate your organization’s usage of or plans for each of the following cloud computing services. (Percent of respondents, N=633)
Currently use Do not currently use, but we have done so within the past two years
Do not currently use but we plan to No use or plans at this time but we are interested
No use, plans, or interest at this time Don’t know
© 2016 by The Enterprise Strategy Group, Inc.
None of the above
Hadoop
Business intelligence
Analytics
Data warehouses
Spark
Databases
4%
34%
38%
39%
41%
43%
43%
For which of the following are you considering public cloud services? (Percent of respondents, N=475, multiple responses accepted)
Big Data in the Cloud
© 2016 by The Enterprise Strategy Group, Inc.
Traditional SQL Database Challenges in the Cloud
ACID compliance is a requirement• Mission critical database applications serve as the lifeline of the business• Delivering high levels of performance is essentialDatabase Performance is a major challenge – how do you address it?1. Increase horsepower
– Database migration– Adds risk and potential for delays– Direct impact on the business
2. Workarounds– Just as expensive as #1– More people, resources, and complexity
3. Read slaves – Band-aid approach– Only work for so long– Workload dependentNone of these options are
futureproof
ClustrixDB Overview
Dave AnselmiDirector of Product Management, Clustrix
ClustrixDB: Scale-Out, Fault-tolerant, MySQL-Compatible
ClustrixDB Overview9
ClustrixDB
ACID Complaint
Transactions & Joins
Optimized for OLTP
Built-In Fault Tolerance
Flex-Up and Flex-Down
Minimal DB Admin
Also runs great inthe Data Center
Built to runin the Cloud
ClustrixDB Technical Overview
Fully Distributed & Consistent Cluster• Fully Consistent, and ACID-compliant database
– Supports transactions– Support joins– Optimized for OLTP– But also supports reporting SQL
• All nodes are equal (no “special” node)• All servers are read/write• All servers accept client connections• Tables & Indexes distributed across all nodes
– Fully automatic distribution, re-balancing& re-protection
ClustrixDB Overview10
Private N
etwork
ClustrixDB on commodity/cloud servers
HW or SW Load Balancer
SQL-based Applications
High Concurrency
Custom:PHP, Java, Ruby, etc
Packaged: Magento, etc
Bill
ions
of R
ows
DatabaseTables
S1 S2S2S3
S3S4S4
S5S5
Intelligent Data Distribution
• Tables auto-split into slices • Every slice has a replica on another node
– Slices are auto distributed, auto-protected
ClustrixDB Overview11
S1
ClustrixDB
S1
S2
S3
S3
S4
S4
S5
Database Capacity
• Easy and simple Flex Up (and Flex Down)– Single minimal interruption of service
• All servers handle writes + reads• Data is automatically rebalanced
across the cluster
ClustrixDB Overview12
S1
ClustrixDB
S2
S5
S1
S2
S3
S3
S4
S4
S5
Built-in Fault Tolerance
• Server node goes down…– Data is automatically rebalanced across
the remaining nodes
• Simply Add new Node – System automatically re-protects– Data is automatically redistributed
ClustrixDB Overview13
S1
ClustrixDB
S2
S5
ClustrixDB Rebalancer: Making the Complex, Simple
Q: How do you ensure data stays well distributed in a clustered environment?
A: You let the Rebalancer handle it!
The Rebalancer automatically:
• Initial Data: Distributes the data into even slices across nodes
• Data Growth: Splits large slices into smaller slices
• Flex-Up/Flex-Down: Moves slices to leverage new nodes and/or evacuate nodes
• Failed Nodes: Re-protects slices to ensure proper replicas exist
• Skewed Data: Re-distributes the data to even out across nodes
• Hotness Detection: Finds hot slices and balances then across nodes
…while the DB stays open for businessPatent 8,543,538Patent 8,554,726
ESG Lab Evaluation
© 2016 by The Enterprise Strategy Group, Inc.
• Same database size configured with the same scripts
• Similar test bed configuration – server configuration differed due to the distributed ClustrixDB architecture
Goals of the ESG Lab Validation
Validate ClustrixDB as a leading cloud database in AWSfor high-value, high-transaction workloads
• Identified a common, real-world OLTP workload
• Compared ClustrixDB to two competing cloud database offerings (referred to as CloudDB1 and CloudDB2)
• Same infrastructure pushing the workload, same time period, same scripts
• Measured the same performance metrics
© 2016 by The Enterprise Strategy Group, Inc.
Performance Test Bed
CloudDB1 and CloudDB2
One r3.8xlarge AWS Instance• 32 cores• 244GB of RAM• 2 x 320GB SSDs
WorkloadDrivers
sysbench
LOAD BALANCER
Four c3.2xlarge AWS Instances• 8 cores• 15GB of RAM• 2 x 80GB SSDs
One database instance with one tableconsisting of 40,000,000 records (20GB)
© 2016 by The Enterprise Strategy Group, Inc.
Transactions/sec• How busy is your database server?• Measures the database activity by tracking the number of serviced requests
Performance Metrics and Scaling the Workload
Average Transaction Latency• How is the end-user experience?• Industry-defined threshold of 20ms• Low, predictable latency tends be more valuable
Performance Curves• Scale-up workload by doubling the concurrent thread count of each test• Increase transactions/sec, but also increase latency
© 2016 by The Enterprise Strategy Group, Inc.
Comparing Single Instance OLTP Workload Performance
20 40 80 160 320 640 12800
2,000
4,000
6,000
8,000
10,000
CloudDB1 CloudDB2 ClustrixDB (4 nodes)Number of concurrent threads
Tran
sacti
ons/
sec
© 2016 by The Enterprise Strategy Group, Inc.
Comparing Scale-out Performance
20 40 80 160 320 640 1280 2560 51200
5,000
10,000
15,000
20,000
25,000
30,000
35,000
40,000
45,000
CloudDB1 CloudDB2 ClustrixDB (4 nodes) 8 nodes 12 nodes 16 nodes 20 nodesNumber of concurrent threads
Tran
sacti
ons/
sec
© 2016 by The Enterprise Strategy Group, Inc.
Near-linear Performance Scalability with ClustrixDB
4 8 12 16 200
5,000
10,000
15,000
20,000
25,000
30,000
35,000
40,000
45,000
50,000
0
20
40
60
80
100
Number of ClustrixDB Nodes
Tran
sacti
ons/
sec
Aver
age
Tran
sacti
on L
aten
cy (m
s)
© 2016 by The Enterprise Strategy Group, Inc.
Clustrix – Making a Representative Benchmark
Peter FriedenbachPerformance Architect, Clustrix
Making a Representative Benchmark
PROPRIETARY AND CONFIDENTIAL23
Why did we choose the workload that we did?• Other venders recently have published performance results with Sysbench.• Things that we think matter:
– Read/Write Mix Matters: Real workloads are a mixture of reads and writes.– Data Size Matters: OLTP databases, while not “big data”, still have record counts of 10 million
or more.– Latency Matters: OLTP workloads demand low latency.
• The ClustrixDB Sysbench Performance Benchmark– Mixed workload: 90% read and 10% writes– Size: 40m records / 20 GB file– Latency: 20ms is the upper range of “acceptable” latency (>3X the initial latency).
• Methodology: Performance curves show a more complete story.– Reveals the “capacity point of the machine”
• The “knee of the curve” where throughput gains succumb to growth in latency.
ClustrixDB Sysbench Benchmark
PROPRIETARY AND CONFIDENTIAL24
ClustrixDB Key Differentiators• MySQL Compatible, Scale-out ACID RDBMS
• Flex-Up and Flex-Down – Flex Licensing allows paying for only the instances you need– Add or remove multiple nodes at a time
• Massively Scaling Writes– ClustrixDB is the only cloud RDBMS that can massively scale
writes in addition to reads– E-commerce, AdTech, IoT are very write-intensive. Clustrix
has multiple satisfied customers in these sectors
• Built for Cloud (any cloud) and Datacenter– One RDBMS wherever the application is deployed
PROPRIETARY AND CONFIDENTIAL25
Thank You
Enterprise Strategy Group | Getting to the bigger truth.™
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© 2016 by The Enterprise Strategy Group, Inc.
Mike Leone, Senior ESG Lab AnalystE-mail: [email protected] Office: 508-244-4814