Technology Summit 30 June 2015, London

Innovation for growing your business

The NoSQL landscape –Document DatabasesStefan Wittmann – Product Manager

The NoSQL landscape

Database Landscape

Data Model Example Requirements Example Uses

Key-value and column Availability, scale and

speed

Big data capture, caching

Document Indexing ability and model

flexibility

Agile (mobile) app

development, mixed data

analytics

NewSQL Consistency Scaling out established

apps

Graph Articulated relationships Analyzing and supporting

social networks,

knowledge intensive

environments

• Proprietary Query Language (No SQL)

• No universal usage

Adoption Barriers

10.000.000

2.000

Our offering

• In addition to the data models we already support we are working

on even more data models:

– Key-Value

– Document

– Graph

Support for new data models

Focus: Document Data Model

• The document model has benefits suited for specific use cases

– Flexibility and Ease-of-Use

• Schemas don’t have to be defined upfront (or ever) and therefore

application developers can quickly setup work environments for their data

and easily adapt to changes in data structure.

– Sparseness

• Attributes with a particular key may appear in some documents within a

collection, but not in others.

– Hierarchical Data

• Structured types may be arrays or objects, nested arbitrarily deep. Data is

stored de-normalized in contrast to relational systems where data is stored

normalized.

– Dynamic Typing

• Values for a particular key have no fixed data type and may vary from

document to document.

Focus on Documents

• Built on two structures

• Collection of name/value pairs

• Ordered list of values

What is a document?

{

"Name" : "John Smith",

"address" : {

"streetAddress": "21 2nd Street",

"city" : "New York",

"state" : "NY",

"postalCode" : 10021

},

"phoneNumber" :

[

{ "type" : "home", "number": "212 555-1234" },

{ "type" : "fax", "number": "646 555-4567" }

]

}

JSON representation

What does a document look like?

Real World

Relational approach

{

„id“:1,

„type“:“meter“,

„timestamp“:“2015-01-01 15:03“

„details“:1

}

{

„id“:1,

„confidence“:3,

„status“:2,

„value“:12345

}

Document Model approach

{

„id“:1,

„type“:“meter“,

„timestamp“:“2015-01-01 15:03“

„details“: {

„confidence“:3,

„status“:2,

„value“:12345

}

}

• Java

• .NET

• Node.js

• COS

• REST

Client Drivers

• JavaScript Object Notation (popularly known as JSON)

[RFC4627] is becoming increasingly important in Web- and

Cloud-based communities for exchanging data between Web-

based applications. This has in turn led to the demands for

storage, retrieval, querying, and manipulation of JSON data in the

context of SQL It is important that SQL respond to these

requirements by providing appropriate extensions for

handling JSON data.

• The SQL/JSON proposals address this comment.

• http://jtc1bigdatasg.nist.gov/_workshop/08_SQL_Support_for_JSON_abstract.pdf

SQL Standard

• No proprietary query language

• We follow a SQL centric approach

– Very close to the draft of the SQL standard committee for JSON SQL

integration

– Set of functions to construct JSON

– Set of functions to query collections

Querying documents

• Construct JSON documents from SQL query results :

– JSON_OBJECT

– JSON_OBJECTAGG

– JSON_ARRAY

– JSON_ARRAYAGG

Publishing JSON

• This query returns one row for each department recorded in the

DEPTS table.

• That row contains a single column, which contains a serialization

of a JSON object having the department number and name.

SELECT

JSON_OBJECT( 'deptno' : deptno, 'deptname' : deptname )

FROM depts

{ "deptno" : 314,"deptname" : "Engineering" }

JSON_OBJECT

• This query returns a JSON object with key value pairs composed

from two columns.

• SELECT JSON_OBJECTAGG (deptname, deptno) FROM depts

• { "Engineering" : 314, "Architecture" : 113, "Accounting" : 12,

"Sales" : 7, "Executives" : 13 }

JSON_OBJECTAGG

• SQL built-in functions for querying JSON data

– JSON_TABLE: returns a SQL table

– JSON_QUERY: returns a SQL string value that corresponds to

a JSON object or a JSON array

– JSON_VALUE: returns a SQL scalar value

• New SQL predicates applicable on JSON data

– IS JSON

– JSON_EXISTS

Querying JSON data

SELECT TOP 10 Name, DOB

FROM JSON_TABLE(

‘People’,

‘{“columns”:

[

{“column”:”Name”,”path”:”$.Name”,”type”:”varchar(50)”},

{“column”:”DOB”,”path”:”$.DOB”,”type”:”DATE”}

]

}’)

ORDER BY Name DESC

Querying a collection

Name DOB

Zimmerman, Norbert Q. 06/02/1938

Yezek, Dave P. 09/16/2005

… …

The Real WorldWhy this matters

• Accept unplanned/unknown data

• Agile Development

• Handle sparse data efficiently

• Fluid data types

• Handle user-defined data

Use Cases

A sneak peek