DataStax & 451 Group Webinar - Real NoSQL Applications in the Enterprise Today

ApacheCassandra Jonathan Ellis, CTO DataStax Matt Aslett, 451 Group

Dec, 7 2011

Real NoSQL Applications in the Enterprise Today.

Welcome and Housekeeping

 We will email the presentation after the webinar

 Please ask questions using the Q&A panel. I will ask the panelists at the end of the presentation.

 You can contact me at [email protected]

Our presenters

  Matt Aslett - Senior Analyst 451 Group Matthew covers data management software for The 451 Group's Information Management practice, including relational and non-relational databases, data warehousing and data caching. Matthew is also an expert in open source software and contributes regularly to reports produced through the 451 Commercial Adoption of Open Source (CAOS) Research Service, as well as to the 451 CAOS Theory blog.

  Jonathan Ellis – CTO DataStax Jonathan is CTO and co-founder at DataStax. Prior to DataStax, Jonathan worked extensively with Apache Cassandra while employed at Racksace. Prior to Rackspace, Jonathan built a multi-petabyte, scalable storage system based on Reed-Solomon encoding for backup provider Mozy. In addition to his work with DataStax, Jonathan is project chair of Apache Cassandra.

© 2011 by The 451 Group. All rights reserved © 2011 by The 451 Group. All rights reserved

451 Research is focused on the business of enterprise IT innovaAon. The company’s analysts provide criAcal and Amely insight into the compeAAve dynamics of innovaAon in emerging technology segments.

The 451 Group

Tier1 Research is a single-‐source research and advisory firm covering the mulA-‐tenant datacenter, hosAng, IT and cloud-‐compuAng sectors, blending the best of industry and financial research.

The UpAme InsAtute is ‘The Global Data Center Authority’ and a pioneer in the creaAon and facilitaAon of end-‐user knowledge communiAes to improve reliability and uninterrupAble availability in datacenter faciliAes.

TheInfoPro is a leading IT advisory and research firm that provides real-‐world perspecAves on the customer and market dynamics of the enterprise informaAon technology landscape, harnessing the collecAve knowledge and insight of leading IT organizaAons worldwide.

ChangeWave Research is a research firm that idenAfies and quanAfies ‘change’ in consumer spending behavior, corporate purchasing, and industry, company and technology trends.

© 2011 by The 451 Group. All rights reserved

451 Research

  MaRhew AsleR •  Senior analyst, enterprise soTware • With The 451 Group since 2007 • www.twiRer.com/masleR


Relevant reports

  NoSQL, NewSQL and Beyond  Assessing the drivers behind the development and adopAon of NoSQL and NewSQL databases, as well as data grid/caching technologies

 Released April 2011  Role of open source in driving innovaAon  [email protected]


NoSQL, NewSQL and Beyond

NoSQL   New breed of non-‐relaAonal database products

  RejecAon of fixed table schema and join operaAons

  Designed to meet scalability requirements of distributed architectures

  And/or schema-‐less data management requirements







NewSQL

 New breed of relaAonal database products

 Retain SQL and ACID  Designed to meet scalability requirements of distributed architectures

 Or improve performance so horizontal scalability is no longer a necessity







NewSQL

 New breed of relaAonal database products

 Retain SQL and ACID  Designed to meet scalability requirements of distributed architectures

 Or improve performance so horizontal scalability is no longer a necessity

… and Beyond

 In-‐memory data grid/cache products  PotenAal primary pla`orm for distributed data management



NoSQL   Big tables – data mapped by row key, column key and Ame stamp

  Key-‐value stores -‐ store keys and associated values

  Document store -‐ stores all data as a single document

  Graph databases -‐ use nodes, properAes and edges to store data and the relaAonships between enAAes







NewSQL  MySQL storage engines -‐ scale-‐up and scale-‐out

 Transparent sharding -‐ reduce to manual effort required to scale

 Appliances -‐ take advantage of improved hardware performance, solid state drives

 New databases -‐ designed specifically for scale-‐out







NewSQL  MySQL storage engines -‐ scale-‐up and scale-‐out

 Transparent sharding -‐ reduce to manual effort required to scale

 Appliances -‐ take advantage of improved hardware performance, solid state drives

 New databases -‐ designed specifically for scale-‐out

Data grid/cache   spectrum of data management capabiliAes, from non-‐persistent data caching to persistent caching, replicaAon, and distributed data and compute grid


Photo credit: Foxtongue on Flickr http://www.flickr.com/photos/foxtongue/4844016087/


SPRAIN

Scalability -‐ Hardware economics

  Example project/service/vendor: •  BigTable, HBase, Riak, MongoDB, Couchbase, Hadoop, Cassandra

•  Amazon RDS, Xeround, SQL Azure, NuoDB

•  Data grid/cache

  Associated use case: •  Large-‐scale distributed data storage •  Analysis of conAnuously updated data •  MulA-‐tenant PaaS data layer


SPRAIN

Performance -‐ MySQL limitaAons

  Example project/service/vendor: •  Hypertable, Couchbase, Riak, Membrain, MongoDB, Redis

•  Data grid/cache •  VoltDB, Clustrix

  Associated use case: •  Real Ame data processing of mixed read/write workloads

•  Data caching •  Large-‐scale data ingesAon


SPRAIN

Relaxed consistency -‐ CAP Theorem

  Example project/service/vendor: •  Dynamo, Voldemort, Cassandra, Riak

•  Amazon SimpleDB

  Associated use case: •  MulA-‐data center replicaAon

•  Service availability •  Non-‐transacAonal data off-‐load


SPRAIN

Agility -‐ polyglot persistence, schema-‐less

  Example project/service/vendor: •  MongoDB, CouchDB, Cassandra, Riak

•  Google App Engine, SimpleDB, SQL Azure

  Associated use case: •  Mobile/remote device synchronizaAon

•  Agile development

•  Data caching


SPRAIN

Intricacy -‐ big data, total data

  Example project/service/vendor: •  Neo4j, GraphDB, InfiniteGraph •  Apache Cassandra, Hadoop, Riak •  VoltDB, Clustrix

  Associated use case: •  Social networking applicaAons •  Geo-‐locaAonal applicaAons •  ConfiguraAon management database


SPRAIN

Necessity -‐ open source

  The failure of exisAng suppliers to address emerging requirements

  Example projects: •  BigTable: Google •  Dynamo: Amazon

•  Cassandra: Facebook •  HBase: Powerset •  Voldemort: LinkedIn

•  Hypertable: Zvents •  Neo4j: Windh Technologies


Use cases – database types


Use cases – new applicaAons

Web applicaAons •  social games •  SaaS •  e-‐commerce systems •  clickstream analysis •  ad and offer targeAng


Use cases – new requirements



Requirements

Data analysis •  read heavy •  batch processing •  analyAcs-‐opAmized •  data locality model


Use cases – new soluAons

Data analysis •  read heavy •  batch processing •  analyAcs-‐opAmized •  data locality model


Requirements

Data analysis •  batch processing •  aggregaAon of mixed data sources •  structured and un/semi-‐structured data •  transform and load


Use cases

Data analysis •  batch processing •  aggregaAon of mixed data sources •  structured and un/semi-‐structured data •  transform and load


Target markets


APACHE CASSANDRA JONATHAN ELLIS

Real NoSQL Applications in the Enterprise Today.

28

Today’s Database Challenge

Navigating the NoSQL waters

 Distributed  Horizontally scalable  Eventually consistent  Non-relational

  Column store   Document stores   Key-value   Graph   … and more

Cassandra: the best for “big data”

 Elegant architecture  Operational flexibility   Industry-leading performance

 You should be using Cassandra for applications requiring   high-performance, realtime queries   scalability past one machine   bulletproof reliability

Bigtable, 2006 Dynamo, 2007

OSS, 2008

Incubator, 2009 TLP, 2010 1.0, October 2011

Cassandra Highlights  Multi-master, multi-DC  Linearly scalable  Larger-than-memory datasets  High performance  Full durability   Integrated caching  Tuneable consistency

A single four-core machine; one million inserts + one million updates

Performance

The Cassandra Difference

Scalable Performance

Oracle Exadata ✖ ✔ ✔

MySQL ✖ ✔ ✔

Sharding ✔ ✔ ✖

MongoDB ✔

Operational Ease

Cost Effective

Cassandra ✔ ✔ ✔

HBase ✔ ✖ ✔

And when it comes to Performance, we’re unmatched.

*

*

✖ ✔

Why Businesses Choose Cassandra Vertical Big-Data

Scale Never Down

Very Fast

Easy to Operate

Non- Structured

Data

Flexible Schema

Multi-DC / Cloud

Cost Effective

Media / Advertising ✔ ✔ ✔ ✔ ✔ ✔ ✔

Telecomm ✔ ✔ ✔ ✔ ✔ ✔ ✔

Financial ✔ ✔ ✔ ✔ ✔ ✔

Social ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔

IT (DaaS) ✔ ✔ ✔ ✔ ✔ ✔ ✔ ✔

Healthcare ✔ ✔ ✔ ✔ ✔

Online Retail ✔ ✔ ✔ ✔ ✔ ✔ The most popular types of applications that use Cassandra are those that… • Are web/SaaS-based, and/or • Collect high volumes of “Data Exhaust” from machine-generated sources

“With Cassandra, we get better business agility, and we don’t have to plan capacity in advance, we don’t need to ask permission of other people to build things for us, and we don’t worry about running out of space or power.”

 Adrian Cockcroft, Cloud Architect

Netflix’s problems  Could not build datacenters fast enough  Made decision to go to cloud (AWS)  Cassandra on AWS is a key infrastructure

component of its globally distributed streaming product.

 Applications include Netflix’s subscriber system, AB testing, and viewing history service (including positions at which members stopped watching a streaming program).

Netflix on Cassandra  Fast  Cheap  Scalable  Flexible  No SPOF

“Without Cassandra, our engineers would’ve had to create something that could scale to our needs, that would’ve prevented us from focusing on building product and solving problems for Backupify’s users, which are far more important tasks.”

 Matt Conway, VP Engineering

Backupify’s problem  Cloud-based utility that enables

businesses and consumers to backup, search and restore the content of popular online applications such as Google Apps, Gmail, Facebook, Twitter, and Blogger

 Needs:   Horizontal scaling   Ability to handle high write loads   Elasticity with no manual sharding

Backupify on Cassandra  Ease of scale enabled engineers to focus

on building great applications  DataStax OpsCenter made it easy to

monitor the health and perf of their cluster   Reliable, redundant and scalable low-

balance data storage helped eliminate down-time

 Ability to offer both backup and storage, but also analysis of data eventually

“You can seamlessly add new nodes and expand your total capacity without deteriorating the performance of the data store. Cassandra has allowed us to scale very effectively.”

 Harry Robertson, Tech Lead

Ooyala’s problem  Ooyala provides a suite of technologies

and services that support content owners in managing, analyzing and monetizing the digital video they publish online

 Needs:   Elasticity, to respond to spikes in data scale   Ability to respond to increasingly

sophisticated analytic needs of customers

Ooyala on Cassandra  Classic “Big Data” problem did not require

re-architecting  Application agility was enabled –

developers spend time building cool apps, not figuring out how to scale

 Enabled more powerful and granular analytics to their customers

“Cassandra has allowed us to build bigger features faster and more reliably, while using less money and without needing to expand our staff.”

 Kyle Ambroff, Sr. Engineer

Formspring’ problem  Users of Formspring engage with and learn

more about each other by asking and responding to questions. With close to 4B responses in the system and 30M unique users, they needed:   To support explosive growth   To seamlessly syndicate user content   To avoid sharding   Application flexiblity

Formspring on Cassandra  No sharding needed – just add nodes to

scale  Performance – the popular users with

many followers saw no speed reduction.  No more memcached!  Flexibility of a schema-optional

architecture is very developer friendly

Why DataStax? DataStax delivers database products and services based on Apache Cassandra from experts who are at the forefront of today's data revolution.

Database Software & Tools Support & Services

  DataStax Enterprise   DataStax Community   DataStax OpsCenter   Drivers & Connectors

  Production Support   Consultative Help   Professional Training   Online Documentation

DataStax Overview   Founded in April 2010   Commercial leader in Apache Cassandra™, the popular

open-source “big data” database   Headquartered in San Francisco Bay area   100+ customers   35+ employees (split between San Fran and Austin)   Home to Apache Cassandra Chair & most committers   Secured $11M in Series B funding in Sep 2011

100+ customers

DataStax Value  The simplest way to get started with Apache

Cassandra: DataStax Community Edition  A smart, integrated platform that provides

Analytics and Real-Time capabilities in the same database, without any resource contention: DataStax Enterprise

 The backing of the Cassandra Experts

DataStax Enterprise 1.  DataStax Enterprise

Database Server

2.  OpsCenter Enterprise Management solution

3.  Expert production support & consultative services

Enterprise Database Server

  Leverages resources on-premise or in the cloud

  Guarantees uptime with a master-less distributed architecture

  Allows for fast application changes via flexible schemas

  Handles structured, semi-structured, and unstructured data

  Provides advanced security   Eliminates the need for separate analytics

system

1

2 3

4

6 5

Real-Time

Analytics

Repl

icat

ion

Enterprise-class database built to handle today’s big-data needs in a cost-effective, easy, and reliable way.

OpsCenter Enterprise

  Visual, browser-based user interface

  Administration tasks carried out in point-and-click fashion

  Allows for visual rebalance of data across a cluster when new nodes are added

  Proactive alerts that warn of impending issues

  Built-in external notification abilities

OpsCenter Enterprise supplies management, monitoring, and control over DataStax Enterprise

Expert Production Support DataStax Enterprise includes production support and consultative services from the Cassandra experts.

 Support service level agreements that range from business hours to 24x7x365

 Consultative support for assistance on architecture, design, and tuning

 Certified quarterly service packs

 Hot-fix support

DataStax Enterprise Compared

Scalable Performance

Oracle Exadata ✖ ✔ ✔

MySQL ✖ ✔ ✔

Sharding ✔ ✔ ✖

MongoDB ✔

Operational Ease

Cost Effective

DataStax Enterprise ✔ ✔ ✔

HBase ✔ ✖ ✔

✖ ✔

Real-Time + Analytics

✔

✖

✔

✖

✖

✖

Oracle NoSQL DB ✔ ✔ ? ✖

DataStax – Your One-Stop Shop  DataStax Enterprise and Community Editions  Professional Training, Expert Consulting  Documentation and Dev Center

  http://www.datastax.com/docs   http://www.datastax.com/dev

 Whitepapers, Case Studies, FAQ’s and more   http://www.datastax.com/resources/whitepapers   http://www.datastax.com/resources/casestudies

Thank you!

Technology

DataStax & 451 Group Webinar - Real NoSQL Applications in the Enterprise Today