This document provides a summary of a presentation about MariaDB AX and new features in MariaDB ColumnStore 1.2. The presentation discusses MariaDB and its history, an overview of big data and analytics, what MariaDB AX is, customer use cases including IHME and a bank in Singapore, and new features coming in ColumnStore 1.2 such as installation simplification, circular joins, and integration with data integration tools.

1. MariaDB AX ユースケース
ColumnStore 1.2新機能
db tech showcase Tokyo 2018
2018-09-21
GOTO Satoru(後藤 智)
Customer Solutions Engineer
MariaDB Corporation

2. Agenda
• MariaDBとは
• Big Data / Analytics 概要
• MariaDB AXとは
• Customer Use Cases
• ColumnStore 1.2新機能

3. MariaDBとは

4. Michael “Monty” Widenius
The Soul of
Open Source
Founder & CTO of MariaDB
MariaDB was created to preserve
openness and community, so that
we can push ahead faster with the
capabilities for tomorrow’s
applications.
”
“

5. GitHub repository
https://github.com/mariadb-corporation/mariadb-columnstore-server
JIRA
https://jira.mariadb.org/projects/MCOL
True Open Source:
ColumnStore GitHub repository / JIRA

6. History of
MySQL & MariaDB
1981 Unireg (base of MySQL code)
1994 SQL インターフェース追加/MySQLに改称
1995 デュアルライセンスにてMySQLリリース
2008 Sunが MySQL AB を買収
2009 2月にMontyらが Sunを離脱, Mariaストレージエンジン
の開発を行うためMonty Program Ab設立
2009 OracleがSun Microsystems買収
2012 MariaDB foundation 設立
2013 主要なLinuxディストリビューションでMySQLから
MariaDBへの移行が進む
2013 Monty Program Ab と SkySQL Ab 合併
2014 SkySQL Ab を MariaDB Corporation に改称
6

7. History of
MySQL & MariaDB
2017 EIB(European Investment Bank) $27M 出資
Alibaba $27M 出資
Microsoft : Platinum Sponsor
2018 MammothDB買収
Alibaba Cloud / ApsaraDB RDS for MariaDB T
Clustrix(ClustrixDB) 買収
7

8. History of MariaDB
Feb 2010 MariaDB 5.1
Nov 2010 MariaDB 5.2
Apr 2012 MariaDB 5.3
Feb 2012 MariaDB 5.5
Mar 2014 MariaDB 10.0
Oct 2015 MariaDB 10.1
May 2017 MariaDB 10.2.6 GA
May 2018 MariaDB 10.3.7 GA
https://downloads.mariadb.org/mariadb/+releases/
https://github.com/MariaDB/server/releases
8

9. Default Database on Leading Linux Distros,
Available on Leading Cloud Platforms
Cloud Services & StacksLinux Distributions

10. 12 million Users in
45 Countries Trust Critical
Business Data to MariaDB TX
Technology & InternetTelecom
Retail & EcommerceTravel
Financial Services Gvmt & Education
Media & Social

11. MariaDB org. sponsors
Platinum Gold

12. Big Data & Analytics overview

13. Transactions
(OLTP)
Analytics
(OLAP)
Learning
(AI/DL)
Order an under kitchen cabinet
water filtering system
(Jan 1, 2019)
Dear Jon Doe,
The carbon filter needs to be replaced
every 6 months for your water filter. Please
click here if you would like us to send one
tomorrow.
(July 1, 2019)
A drone maps out optimal route using
geospatial data, weather data, other
traffic in the air, location data to
deliver the filter at your door steps.
(July 2, 2019)

14. • さまざまな分析手法やアルゴリズムを駆使、データ中の特定パターンや相関
関係などを抽出すること
• 推測/直感に頼らない
• 最適な意思決定を助ける
記述的/診断的アナリティクス 予測的 処方的
Questions 何が起きたのか?
なぜ起きたのか?
何が起こるのか?
なぜ起こるのか?
何をすべきか?
なぜやるべきか?
Enablers Business Reporting
Dashboards and Scorecards
Data & Text mining
Forecasting
Decision Modeling
Expert systems
Outcomes Well defined business problems and
outcomes
Accurate projections of future
states and conditions
Best possible business decisions
and transactions
Analyticsとは

15. • Online Advertising
• Advertisement Targeting
• Spend Optimization
• Page View Guarantees
• Ad selection
• Fraud Prediction
• Traffic Quality
• Telecom
• Churn Prediction
• Expansion/Growth Planning
• Bundle Selection
• Advertisement Targeting
• Network Analysis
• Fault Prediction
• Manufacturing
• Production Planning
• Processing Optimization
• Early Event Detection
• Risk Reduction
• Inventory Optimization
• Capital Minimization
• Price Projections
• Corporate Finance
• Optimize Cash Flow
• Investment Optimization
• Human Resource
• Workforce Analytics
• Talent Selection
• Retention and Churn Prediction
Analytic Use Cases

16. Analytic Use Cases
• Sports
• Moneyball (Sabermetrics)
• Social - Flavors
• Sentiment Analysis
• Customer Segmentation
• Oil
• Reservoir location estimation
• Reservoir size estimation
• Demand Prediction
• Energy
• Demand Prediction
• Production Estimation
• Fault Prediction
• Finance
• Portfolio Planning
• Risk Minimization
• Next Best Offer
• Capital Minimization
• Price Projections

17. Analytics is not a silver bullet!
Data
Technology
Line of Business
• Garbage in - Garbage out (Data quality)
• Maslow’s hammer (Data Science/Algorithms)
• Lack of domain experts

18. Limited real time analytics
Slow releases of product innovation
Expensive hardware and software
Data Warehouses
Hadoop / NoSQL
Data Analytics Technologies
Hard to use
TeraData, Vertica, GreenPlum
Cloudera, Hortonworks, MapR
High performance interactive and real-time analytics
High speed data ingestion
Elasticity and Agility
Mature SQL interfaces, Large Talent Pool
Limited SQL support
Difficult to install/manage
Limited Talent Pool
Data Lake w/ No Data Management
Emerging: Cloud, In Memory
RedShift, SnowFlake, BigQuery, MemSQL

19. MariaDB AX
Analytics -
simple, fast, scalable…
and open source

20. MariaDB TX MariaDB AX
for Transactional workloads
● MariaDB Server
● MariaDB MaxScale
● database connectors
● services
● support
● tools
for Analytic workloads
● MariaDB Server
● MariaDB ColumnStore
● MariaDB MaxScale
● database connectors
● services
● support
● tools

21. What is MariaDB AX ?
● MariaDB ColumnStore releases
● MariaDB database proxy, MaxScale
● MariaDB Connectors
● 24x7x365 support
● 30-minute emergency response time
● Mission-critical patching
● Guaranteed version support
● Management and monitoring tools
● Installers
Modern data warehousing solution for large scale analytics
MariaDB ColumnStore
MariaDB MaxScale
MariaDB Connectors

22. AX(ColumnStore) History
2016 Dec
MariaDB ports InfiniDB as
storage engine
MariaDB ColumnStore 1.0
● High Performance
Analytics
● High speed ingestion
● Distributed, MPP
MariaDB AX
● ColumnStore
● MaxScale
2017 Dec
MariaDB ColumnStore 1.1
● Streaming ingestion
● Spark Integration
● User Defined Aggregate
Function
● Backup/Restore Tool
● GlusterFS support
2014 Oct
MariaDB Corporation
takes over InfiniDB
support contracts

23. MariaDB ColumnStore
Distributed Data Storage
Local Storage | SAN | NAS | AWS EBS | GlusterFS
BI Tool SQL Client Custom
Big Data App
Application
MariaDB
SQL Front
End - UM
Distributed
Query Engine
- PM
Data Storage
Columnar
Massively Parallel Processing(MPP)
Distributed storage
Mature SQL support
High performance analytics queries
Parallel high speed data ingestion
Batch and Streaming data loading
Compression
Built in High Availability
Enterprise grade security
High performance distributed columnar storage engine for
analytical use cases

24. Customer Use Cases

25. MariaDB AX(ColumnStore) Customers
MarTech Technology/Internet/IoTFinance Health Care
Services
Public Sector

26. IHME - Institute of Health Metrics and Evaluation
UM/PM UM/PM UM/PM UM/PM
Application Application Application Application Application
Max
Scale
● Use Case:
○ Public Health Data Analytics
● Competition:
○ Percona InnoDB, MemSQL
● Why ColumnStore:
○ InnoDB (on Percona) reached
performance limit with max tuning
for 4 TB data
○ ColumnStore easy to use
● Data Volume: Started with 4.2 TB, with
goal to go to 30TB of data in 5 years
Wrong database/storage engine (MySQL InnoDB) for analytics use case
http://www.healthdata.org/results/data-visualizations

27. IHME - Institute of Health Metrics and Evaluation
M|17: Real World: How IHME Uses MariaDB for Analysis and Data
https://vimeo.com/213881969
(42 min. recording)
IHME Believes Open Source MariaDB ColumnStore Is The Future
of Data Warehousing
https://mariadb.com/ja/node/1482

28. SpendHQ
• Use Case
– Strategic sourcing, spend analytics, and procurement
process transformation
– Moving away from MySQL InnoDB
• Why MariaDB ColumnStore
– High Performance Analytics
– No internal expertise on MariaDB AX
Wrong database/storage engine (MySQL InnoDB) for analytics use case

29. TX offloading
Max
Scale
Applications
Production
Galera Cluster
CDC Streaming
ColumnStore
UM
PM
Max
Scale
Max
Scale
Transactional workload running out of steam, in need of analytics with better performance
TX Data : 7 to 14 days
AX data: 14 days to 2 years

30. Leading Bank in Singapore
Aging Legacy system & Challenges with Hadoop
MariaDB AX
UM
PM
ERP
CRM
IBDT
HDFS
MapReduce Hive HBase
Max
Scale
Load subset of
Data into
ColumnStore
Qlik
SAS
Homegrown
Apps
Python
R
• Data Volume: 4 TB per year
• Data retention: Min 2 years, Max 7 years
1. Paying too much for analytics with TeraData, worried about aging tech of GreenPlum
● TeraData used for 5 TB data only due to cost. TeraData is not open source
● GreenPlum is aging and does not have active development
2. Challenges with Hadoop:
● Cannot do high performance interactive analytics
● Adding storage requires adding costly compute nodes
Banking
apps

31. ColumnStore
1.2 新機能

32. 2018 MariaDB Corp- Confidential
Coming in ColumnStore 1.2 (Dec 2018)
● Install Simplification
● Circular Join
● DATETIME - Time Datatype up to microseconds
● Regression Functions
● ETL/BI Partners: Pentaho, Informatica
● mcsimport - Data loads faster than cpimport
● DBaaS Enablement
● Integration with MariaDB Server(TX)

33. Pentaho Kettle Adapter(beta) in PDI8.0 CE

34. Download
https://mariadb.com/downloads/mariadb-ax
1
Read the Technical overviews
https://mariadb.com/resources/datasheets-guides
2
Search the Knowledge Base
https://mariadb.com/kb
3
Watch a Webinar
https://mariadb.com/resources/webinars
4
Get Started with MariaDB AX

35. A15: JPMUG (Japan MariaDB User Group) 代表 川野様
MariaDB ColumnStore を使いこなそう
https://www.slideshare.net/KAWANOKAZUYUKI/mariadb-columnstore-115516280

36. Thank you