How to Handle NoSQL with a Relational Database

Handling NoSQL with
a Relational Database
Thomas Boyd
Director, Technical Marketing
MariaDB Corporation

Agenda
● Relational Databases & SQL
● Document Databases & NoSQL
● MariaDB: SQL and NoSQL together
○ Scalability
○ JSON Support
○ Node.js Integration
● Q & A

Proven Technology
● 1970: “Relational Completeness of Data Base Sublanguages”
● ANSI managed Structured Query Language (SQL)
● Large ecosystem of RDBMS Vendors and Tools
● Large Talent Pool
○ Developers & Data Modelers
○ DBAs/Operators
○ Architects

Relational: Modeling
Orders
Id Number Rep_Id
1 1001 4
2 1002 8
3 1003 5
4 1004 7
Order_Lines
Order_ID Line_ID Line_Number Prodcut_ID Qty Price
1 1 1 101 1 5.55
1 2 2 123 10 12
1 3 3 103 1 7.25
2 4 1 101 2 11.05
2 5 2 114 3 3.45

NoSQL & Document Databases
● NoSQL
○ Key-Value, Wide Column, Document, and more
● Drivers of Popularity of Document Databases
○ Scalability
○ JSON Support & Schema-less
○ Drivers and Modern Application Stacks (Node.js)

Document: Modeling
{
order_ID: 1,
number: 101
sales_rep: {first_name: “John”, last_name: “Smith”, …},
order_Lines: [ {line_id: 1, number: 101, …},
{line_id: 2, number: 102, …},
{line_id: 3, number: 103, …}]
}

NoSQL: Caveats
● Limited Transaction support
● Proprietary and inefficient SQL access
● Fewer integrations and smaller ecosystem
● Smaller talent pool
● Down-sides to documents and schema-less
○ Data hygiene
○ Storage size and query efficiency
○ Expensive updates of denormalized data

MariaDB: Combining
SQL & NoSQL

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

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

Scalability
● MariaDB has multiple options for Scalability
○ Read Scalability with Replicas
○ Write Scalability with Spider (Partitioning/Sharding)
○ Scaling for Big Data Analytics with MariaDB ColumnStore
○ Other techniques via MaxScale router
○ Vertical scaling

Scalability: Read Scalability via Replicas
MariaDB Platform
MariaDB Server
(slave)
MariaDB Server
(master)
MariaDB Server
(slave)
MariaDB MaxScale

Scalability: Write Scalability via Spider
● Range
● Hash
● Key
● List
MariaDB Platform
MariaDB ServerMariaDB Server MariaDB Server
MariaDB Server
MariaDB MaxScale
Spider Storage Engine

Scalability: Big Data via Platform &
ColumnStore
MariaDB Platform
MariaDB MaxScale
CDC
MariaDB Server
InnoDB
MariaDB Server
ColumnStore
Transactional Analytical

Structured and semi-structured data
with relational + JSON
Structured Semi-structured

Structured and semi-structured data
with relational + JSON
Structure data described
by the schema
Structured described
by the data

JSON Example: definition
CREATE TABLE IF NOT EXISTS products (
id INT NOT NULL PRIMARY KEY AUTO_INCREMENT,
type VARCHAR(1) NOT NULL,
name VARCHAR(40) NOT NULL,
format VARCHAR(20) NOT NULL,
price FLOAT(5, 2) NOT NULL,
attr JSON NOT NULL);

Example: create
INSERT INTO products (type, name, format, price, attr) VALUES
('M', 'Aliens', 'Blu-ray', 13.99,'{"video": {"resolution": "1080p", "aspectRatio": "1.85:1"},
"cuts": [{"name": "Theatrical", "runtime": 138}, {"name": "Special Edition", "runtime":
155}], "audio": ["DTS HD", "Dolby Surround"]}');
('B', 'Foundation', 'Paperback', 7.99, '{"author": "Isaac Asimov", "page_count": 296}');

Example: read field
SELECT name, format, price,
JSON_VALUE(attr, '$.video.aspectRatio') AS aspect_ratio
FROM products
WHERE type = 'M';
name format price aspect_ratio
Aliens Blu-ray 13.99 1.85:1

Example: null field
SELECT type, name, format, price,
JSON_VALUE(attr,$.video.aspectRatio') AS aspect_ratio
FROM products;
type name format price aspect_ratio
M Aliens Blu-ray 13.99 1.85:1
B Foundation Paperback 7.99 NULL

Example: contains value
SELECT id, name, format, price
FROM products
WHERE type = 'M' AND
JSON_CONTAINS(attr, '"DTS HD"', '$.audio') = 1;

Example: read array
JSON_QUERY(attr, '$.audio') AS audio
FROM products
WHERE type = 'M';
name format price audio
Aliens Blu-ray 13.99 [
"DTS HD",
"Dolby Surround"
]

Example: read array element
JSON_VALUE(attr, '$.audio[0]') AS default_audio
FROM products
WHERE type = 'M';
name format price audio
Aliens Blu-ray 13.99 DTS HD

Example: read object
JSON_QUERY(attr, '$.video') AS video
FROM products
WHERE type = 'M';
name format price video
Aliens Blu-ray 13.99 {
"resolution": "1080p",
"aspectRatio": "1.85:1"
}

Example: field equals
SELECT id, name, format, price
FROM products
WHERE type = 'M' AND
JSON_VALUE(attr, '$.video.resolution') = '1080p';

Example: indexing (1/2)
ALTER TABLE products ADD COLUMN
video_resolution VARCHAR(5) AS (JSON_VALUE(attr, '$.video.resolution')) VIRTUAL;
EXPLAIN SELECT name, format, price
FROM products
WHERE video_resolution = '1080p';
id select_type table type possible_keys
1 SIMPLE products ALL NULL

Example: indexing (2/2)
CREATE INDEX resolutions ON products(video_resolution);
EXPLAIN SELECT name, format, price
FROM products
WHERE video_resolution = '1080p';
id select_type table ref possible_keys
1 SIMPLE products ref resolutions

Example: insert field
UPDATE products
SET attr = JSON_INSERT(attr, '$.disks', 1)
WHERE id = 1;
name format price disks
Aliens Blu-ray 13.99 1
JSON_VALUE(attr, '$.disks') AS disks
FROM products
WHERE type = 'M';

Example: insert array
UPDATE products
SET attr =JSON_INSERT(attr, '$.languages',
JSON_ARRAY('English', 'French'))
WHERE id = 1;
name format price languages
"English",
"French"
]
JSON_QUERY(attr, '$.languages')
AS languages
FROM products
WHERE type = 'M';

Example: add array element
UPDATE products
SET attr = JSON_ARRAY_APPEND(attr,
'$.languages', 'Spanish')
WHERE id = 1;
"English",
"French",
"Spanish"
]
AS languages
FROM products
WHERE type = 'M';

Example: remove array element
UPDATE products
SET attr = JSON_REMOVE(attr, '$.languages[0]')
WHERE id = 1;
"French",
"Spanish"
]
AS languages
FROM products
WHERE type = 'M';

Example: relational to JSON
SELECT JSON_OBJECT('name', name, 'format', format, 'price', price) AS data
FROM products
WHERE type = 'M';
data
{
"name": "Tron",
"format": "Blu-ray",
"price": 29.99
}

Example: relational + JSON
SELECT JSON_OBJECT('name', name, 'format', format, 'price', price, 'resolution',
JSON_VALUE(attr, '$.video.resolution')) AS data
FROM products
WHERE type = 'M';
data
{
"name": "Aliens",
"price": 13.99,
"resolution": "1080p"
}

Example: relational + JSON
SELECT JSON_MERGE(
JSON_OBJECT(
'name', name,
'format', format),
attr) AS data
FROM products
WHERE type = 'M';
data
{
"name": "Tron",
"video": {
"resolution": "1080p",
"aspectRatio": "1.85:1"},
"cuts": [
{"name": "Theatrical", "runtime": 138},
{"name": "Special Edition", "runtime": 155}],
"audio": [
"DTS HD",
"Dolby Surround"]}

Example: constraints (1/3)
ALTER TABLE products ADD CONSTRAINT check_attr
CHECK (
type != 'M' or (type = 'M' and
JSON_TYPE(JSON_QUERY(attr, '$.video')) = 'OBJECT' and
JSON_TYPE(JSON_QUERY(attr, '$.cuts')) = 'ARRAY' and
JSON_TYPE(JSON_QUERY(attr, '$.audio')) = 'ARRAY' and
JSON_TYPE(JSON_VALUE(attr, '$.disks')) = 'INTEGER' and
JSON_EXISTS(attr, '$.video.resolution') = 1 and
JSON_EXISTS(attr, '$.video.aspectRatio') = 1 and
JSON_LENGTH(JSON_QUERY(attr, '$.cuts')) > 0 and
JSON_LENGTH(JSON_QUERY(attr, '$.audio')) > 0));

('M', 'Tron', 'Blu-ray', 29.99, '{"video": {"aspectRatio": "2.21:1"}, "cuts": [{"name": "Theatrical",
"runtime": 96}], "audio": ["DTS HD", "Dolby Digital"], "disks": 1}');
ERROR 4025 (23000): CONSTRAINT `check_attr` failed for `test`.`products`
no resolution field!

('M', 'Tron', 'Blu-ray', 29.99, '{"video": {"resolution": "1080p", "aspectRatio": "2.21:1"}, "cuts":
[{"name": "Theatrical", "runtime": 96}], "audio": ["DTS HD", "Dolby Digital"], "disks": "one"}');
ERROR 4038 (HY000): Syntax error in JSON text in argument 1 to function 'json_type' at
position 1
"one" is not a number!

• Ryan Dahl, JSConf 2009
• Event Loop, Callbacks & Non-blocking IO
• Different mindset from synchronous
programming

GA MariaDB Access since 2014
2011-2013: MySQL Development
Jan 2014: MySQL GA Release
Sep 2016: MySQL2 GA Release
Dec 2018: MariaDB RC
Jan 2019: MariaDB GA Release

Node.js Driver
● MariaDB Released Driver available Jan 2019
● Increased performance
○ Pipelining of statements
○ Bulk operations
● ORM Support: Sequelize
● Frameworks: Feathers.js

Sequelize Model Definition
class Task extends Model {}
Task.init({
title: Sequelize.STRING,
description: Sequelize.TEXT,
deadline: Sequelize.DATE
}, { sequelize, modelName: 'task' })
http://docs.sequelizejs.com/

Installation js-demo$ npm install mariadb
+ mariadb@2.0.2-rc
updated 1 package and audited 180 packages in 1.321s
found 0 vulnerabilities
js-demo$
• NPM Package Manager
• Download at https://mariadb.com/downloads/#connectors
js-demo$ tar -xzf mariadb-connector-nodejs-2.0.2-rc.tar.gz
js-demo$ cd mariadb-connector-nodejs-2.0.2-rc
js-demo$ npm link
js-demo$ cd <project directory>
js-demo$ npm link mariadb

Resources
https://mariadb.com
https://mariadb.com/resources/
https://mariadb.com/contact

How to Handle NoSQL with a Relational Database

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