(SQL Server) Nosql

Relational to NoSQL: Getting started from SQL Server Shane Johnson Sr. Product Marketing Manager Couchbase Today’s agenda

§ Why NoSQL? § Identifying the right application § Modeling your data § Accessing your data § Installing and scaling your database § Monitoring and managing your deployment § Q & A

Shane Johnson Senior Product Marketing Manager Couchbase (since Dec 2013)

Experience: - Proud Red Hatter - Consulting (Architect) - Transitioned to Marketing (Technical Manager) - Passionate about Open Source - Expertise - Java and Distributed Systems

Couchbase is the company behind Couchbase Server & Couchbase Mobile • Open source JSON database • Founded 2010 • 500+ enterprise customers globally

Some of our customers:

Couchbase Server can be deployed as: Document database Key-value store Distributed cache

§ No SQL? No. § Distributed (most) § Not only SQL? Not really. – Scaled out, not up § Non relational? Yes. • Elasticity and commodity hardware – Partitioned and replicated • Scalability, performance, availability § Schema-less (most) – Flexible model – JSON (some)

Enterprises are adopting NoSQL for mission critical applications

Media & Publishing eCommerce Hospitality

§ Gannett, publisher of USA Today and 90+ media properties, replaced relational database technology with NoSQL to power its digital publishing platform. § Marriott deployed NoSQL to modernize its hotel reservation system that supports $38 billion in annual bookings. § FHLBank Topeka leverages NoSQL on top of SQL Server to speed up access to customer financial data for its 770 member banks § Cars.com, with over 30 million visits per month, replaced SQL Server with NoSQL to store customer and vehicle data § Vente-privee.com improved the customer experience of its 18 million members by replacing SQL Server with NoSQL for better performance

Technology Drivers Technical Needs

§ Customers are going online § Develop with agility § The Internet is connecting everything – Flexibility + Simplicity § Big Data is getting bigger – Easier + Faster § Applications are moving to the cloud § Operate at any scale § The world has gone mobile – Elasticity + Availability – Performance at scale – Always-on, global deployment

Business Needs

§ Easier to scale 3 nodes to 100s, 1 data center to many, commodity hardware § Better performance integrated caching, memory-optimized indexes, memory-based replication § Up to 40x lower cost open source, subscription-based, per instance (not per core) § Cross-platform runs on Windows or Linux (Red Hat, Ubuntu, Debian, etc) § Greater agility JSON-based data model, SQL-based query language

§ Identify the right application § Model your data § Access your data § Install and scale your database § Monitor and manage your deployment

Have one or more of the following characteristics or requirements: Iterate faster Supports users anywhere and Send and receive JSON everywhere Provide low latency at any throughput Be available 24x7 Support many concurrent users Store terabytes of data Read and write to multiple data centers Examples: Application § High performance, high availability caching service § Small, independent application with a narrow scope § Logical or physical service within a large application Service Service Service § Global service that powers multiple applications

RDMBS NoSQL

Relational (SQL Server) NoSQL (Couchbase) Failover Cluster Cluster Availability Group Cluster Database Bucket Table Bucket Row (Tuple) Document (JSON) Primary Key Object ID IDENTITY Counter Indexed View View SQL N1QL

Same document type, Different fields

• Different types • Optional • On-demand

Tip: Add a version field to track changes.

{“docType”: “user”, “docVersion”: “1”, …} {“docType”: “user”, “docVersion”: “2”, …}

Relational database Document database

• Modify the database schema • Modify the interface (e.g. HTML5/JS) • Modify the application code (e.g. Java) • Modify the interface (e.g. HTML5/JS)

Best Practices Examples

• Natural Keys • author::shane • Human Readable • author::shane::blogs • Deterministic • blog::nosql_fueled_hadoop • Semantic • blog::nosql_fueled_hadoop::comments What about identity columns?

1. Document nextAuthorIdDoc= bucket.counter(“authorIdCounter”, 1); 2. Long nextAuthorId = nextAuthorIdDoc.content(); 3. String authDocId = “author::” + nextAuthorId; // author::101

Tip: Increment the counter by 10, 20, etc. instead of doing it for every insert.

Bottom up Top down

Author Author (FK x2)

Blog (FK) Blog (FK) Blog (FK x2) Blog

Comment (FK) Comment (FK) Comment Comment

If… Then… Relationship is one-to-one or one-to-many Store related data as nested objects

Relationship is many-to-one or many-to-many Store related data as separate documents

Data reads are mostly parent fields Store children as separate documents

Data reads are mostly parent + child fields Store children as nested objects

Data writes are mostly parent or child (not both) Store children as separate documents

Data writes are mostly parent and child (both) Store children as nested objects

§ Are they a lot of concurrent writes, continuous updates? § Store children as separate documents

Blog Blog Thread § Thread § { { Comment “docType”: “blog”, “docType”: “thread”, § Comment “author”: “author::shane”, “comments”: [ § Thread “title”: “Couchbase Wins”, { § Comment “threads”: [ “visitor”: “Brendan Bond”, § Comment “blog::couchbase_wins::threads::001”, “text”: “This blog is amazing!” “blog::couchbase_wins::threads::002” “replies”: [ } { “user”: “Dustin Johnson”, “text”: “No, it is not.” }] } ©2015 Couchbase Inc. } 21 Access your data

We’ll focus on these three for now.

Key-Value N1QL Views Full Text Geospatial (CRUD) (Query) (Query) (Search) (Search)

Indexes MapReduce Indexes MapReduce

Documents

§ Access data via topology-aware smart clients § Maintains an up-to-date cluster map § Communicates directly with database nodes – no proxies, no routers, etc. § Available for Java, Node.js, PHP, .NET, Python, C, Go, and more § With standard, certified JDBC/ODBC drivers (if you want to)

Working with document objects requires less code, provides more flexibility.

* JSON serialization via Boon.

Feature SQL N1QL JOIN ✔ ✔ TRANSFORM ✔ ✔ FILTER ✔ ✔ AGGREGATE ✔ ✔ SORT ✔ ✔ SUBQUERIES ✔ ✔ PAGINATION ✔ ✔ OPERATORS ✔ ✔ FUNCTIONS ✔ ✔

_context.Query().Where(u => u.status == “Platinum”)

from user in _context.Query() join account in _context.Query() on user.accountIdequals N1QlFunctions.Key(account) into userGroup from accounts in userGroup.DefaultIfEmpty() where (account.type == “Visa” || account.type== “MasterCard”) select new { firstName = user.firstName, lastName = user.LastName };

from user in _context.Query() join address in _context.Query

() on user.addresses.shipping.addressId equals N1QlFunctions.Key(address) into addressGroup from address in addressGroup.DefaultIfEmpty() where address.state == “CA” select new { firstName = user.firstName, lastName = user.LastName };

Simple Functional

Compound Partial

What if indexed views worked great with write intensive workloads?

And you could use COUNT, ORDER BY, and everything else…

COUNT ?!?

Concept Strategies & Best Practices Key Value Operations provide the best • Create an effective key naming strategy possible performance • Create an optimized data model

Incremental MapReduce (Views) are well • Ideal for large data sets, the entire data set suited to aggregation • Can be used to create complex secondary indexes

N1QL queries provide the most flexibility – • Query data regardless of how it is modeled everything else • Remember to create indexes, leverage covering indexes where possible

1. Download 2. Install 3. Configure 4. Cluster / Scale 5. Rebalance

Admin screenshot – add node

§ Multiple Data Centers § Cluster per data center § Replicate between clusters § Unidirectional / bidirectional § Master / Master § Local reads and writes § Ring § Hub-and-spoke § Mesh § Combination § Built-in

§ Management, monitoring, and § Configuration configuration – Authentication and authorization – Cluster / node / bucket / views – Auditing – Cross data center replication (XDCR) § Monitoring – Database performance, network – View and collect log information utilization, resource utilization § Tooling § Tasks – cbbackup & cbrestore – Add and remove nodes – cbcollect_info & cbdstats – Failover nodes – cbq – Rebalance cluster – cbtransfer – and more…

Conduct a Successful Proof of Concept Measure your Return on Investment

1. Select a use case and application § Greater agility? 2. Define the success criteria § Faster time to market? 3. Understand the data § Easier scalability? 4. Identify the access patterns § Better performance? 5. Review the architecture § Better availability? § Lower costs?

Couchbase Server 4.5 Beta www.couchbase.com/next

Easier, more efficient querying Faster, more powerful indexing Integrated query editor Memory-optimized indexes Indexed joins Array indexing Integrated full-text search Circular reuse Ready your own writes Better, more comprehensive admin Simpler, more advanced data access Query monitoring Partial updates, reads, etc. Faster backup and restore X.509 certificates Role-based access control

“How to Get Started” White Paper Download Couchbase software: http://www.couchbase.com/binaries/content/assets/us/product/couchbase-server- http://www.couchbase.com/nosql-databases/downloads 4.0/sql_servertonosql.pdf