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The Leading Scale-out SQL Database
Engineered for the Cloud
Robin Purohit
CEO and President
SCALE-OUT DATABASES ARE THE RIGHT APPROACH
UNLESS YOU HAVE UMLIMITED MONEY TO SPEND
NoSQL NewSQL Hadoop
FOR HYPER-SCALE WEB AND MOBILE APPLICATIONS
Cloud Makes It Possible Do This Quickly and Pay-as-you-go
Great Idea Billions of Transactions
and Rows
Smarter
Application
Ad Hoc
Reporting
SCALE-OUT SQL DATABASE FOR OPERATIONAL DATA
MASSIVE
TRANSACTION
VOLUME
REAL-TIME
ANALYTICS
ACID, SQL AND MYSQL
SELF-MANAGING
BUILT-IN INSTRUMENTATION
SCALE-OUT SQL
Add nodes as demand grows
Automated recovery on failure
OPERATIONAL DATABASE
E-commerce
EXAMPLES APPLICATION SEGMENTS
BATTLED TESTED LESSONS
Consumer Web Advertising Analytics
BUSTING THE MYTH - SQL CAN SCALE
• 20 million+ users / 70,000+ TPS
• Write heavy workload; 1TB+ writes / day
Massive Transaction Scale Real-Time Analytics
MIXED
WORKLOADS
IF YOU DON’T BELIEVE US – BELIEVE GOOGLE
F1 Based on “SPANNER” for Ad Words
http://www.theregister.co.uk/2013/08/30/google_f1_deepdive/
“100s of applications on over 100TB serving up 100s of thousands of requests per second
+ SQL queries that scans tens of trillions of data rows a day”
HOW TO CHOOSE
THE RIGHT TOOL
FOR THE JOB?
E-COMERCE EXAMPLE (SQL NORMALIZATION + JOIN = GOOD)
Customers
(many)
Products
(many or few
& may require
flexibility)
Orders
(many)
Reviews
(many)
Problem is naturally relational - Orders, Reviews are
for products by customers
What questions do you have?
• Do you want to know all reviews for a product
along with the customer who wrote it (Product X
Review X Customer)
• What about most popular products in San
Francisco, or last 10 orders by a customer?
What Flexibility do you need?
• Maybe all products have different attributes
WHAT DATA and WHAT QUESTIONS?
How SIMPLY do the QUESTIONS need to be answered?
MAP REDUCE OR SQL?
And how many
lines of code?
WHEN do you want the QUESTIONS answered?
How COMPLEX is the Question?
NoSQL
Key-Value, Document
NewSQL
e.g. Clustrix
Warehousing Analytics
Hadoop, Vertica, Redshift
Query Complexity
In Memory Analytics
Reads and Writes Real-Time Analytics Batch Analytics
milliseconds seconds minutes Hours
ETL
Hadoop
Key-Value
SQL
Warehousing
Vertica
SIZE and FLEXIBILITY and QUERIES
SIZE FLEXIBILITY
NewSQL10s of TBS
100s of TBS
Petabytes
Key-Value
Hadoop
Document /
Tabular
Relational Schema,
Online schema
changes
Schema-less
NEWSQL
Rows with
different columns
QUERY ABILITY
Simple lookup
Indexed lookup
Joins and
complex
Analytics
With Flexibility,
you Lose the sophisticated
SQL Query optimizer
RIGHT TOOL FOR THE JOB
NoSQL NewSQL Hadoop Columnar
OPERATIONAL DATA BATCH ANALYSIS
With Alot More SQL
Clustrix Technical
Resources
docs.clustrix.com

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Clustrix Big Data Podcast

  • 1. The Leading Scale-out SQL Database Engineered for the Cloud Robin Purohit CEO and President
  • 2. SCALE-OUT DATABASES ARE THE RIGHT APPROACH UNLESS YOU HAVE UMLIMITED MONEY TO SPEND NoSQL NewSQL Hadoop
  • 3. FOR HYPER-SCALE WEB AND MOBILE APPLICATIONS Cloud Makes It Possible Do This Quickly and Pay-as-you-go Great Idea Billions of Transactions and Rows Smarter Application Ad Hoc Reporting
  • 4. SCALE-OUT SQL DATABASE FOR OPERATIONAL DATA MASSIVE TRANSACTION VOLUME REAL-TIME ANALYTICS ACID, SQL AND MYSQL SELF-MANAGING BUILT-IN INSTRUMENTATION SCALE-OUT SQL Add nodes as demand grows Automated recovery on failure OPERATIONAL DATABASE
  • 5. E-commerce EXAMPLES APPLICATION SEGMENTS BATTLED TESTED LESSONS Consumer Web Advertising Analytics
  • 6. BUSTING THE MYTH - SQL CAN SCALE • 20 million+ users / 70,000+ TPS • Write heavy workload; 1TB+ writes / day Massive Transaction Scale Real-Time Analytics MIXED WORKLOADS
  • 7. IF YOU DON’T BELIEVE US – BELIEVE GOOGLE F1 Based on “SPANNER” for Ad Words http://www.theregister.co.uk/2013/08/30/google_f1_deepdive/ “100s of applications on over 100TB serving up 100s of thousands of requests per second + SQL queries that scans tens of trillions of data rows a day”
  • 8. HOW TO CHOOSE THE RIGHT TOOL FOR THE JOB?
  • 9. E-COMERCE EXAMPLE (SQL NORMALIZATION + JOIN = GOOD) Customers (many) Products (many or few & may require flexibility) Orders (many) Reviews (many) Problem is naturally relational - Orders, Reviews are for products by customers What questions do you have? • Do you want to know all reviews for a product along with the customer who wrote it (Product X Review X Customer) • What about most popular products in San Francisco, or last 10 orders by a customer? What Flexibility do you need? • Maybe all products have different attributes WHAT DATA and WHAT QUESTIONS?
  • 10. How SIMPLY do the QUESTIONS need to be answered? MAP REDUCE OR SQL? And how many lines of code?
  • 11. WHEN do you want the QUESTIONS answered? How COMPLEX is the Question? NoSQL Key-Value, Document NewSQL e.g. Clustrix Warehousing Analytics Hadoop, Vertica, Redshift Query Complexity In Memory Analytics Reads and Writes Real-Time Analytics Batch Analytics milliseconds seconds minutes Hours ETL
  • 12. Hadoop Key-Value SQL Warehousing Vertica SIZE and FLEXIBILITY and QUERIES SIZE FLEXIBILITY NewSQL10s of TBS 100s of TBS Petabytes Key-Value Hadoop Document / Tabular Relational Schema, Online schema changes Schema-less NEWSQL Rows with different columns QUERY ABILITY Simple lookup Indexed lookup Joins and complex Analytics With Flexibility, you Lose the sophisticated SQL Query optimizer
  • 13. RIGHT TOOL FOR THE JOB NoSQL NewSQL Hadoop Columnar OPERATIONAL DATA BATCH ANALYSIS With Alot More SQL

Notas do Editor

  1. This slide conveys what we believe are the key characteristics of the ideal database for real world workloadsand the Cloud. In other words, this is the “wish list” for the ideal database.Key points to emphasizeScale-Out SQL is the way to goClustrix offers a scale-out SQL database that lets you simply add more nodes* to your cluster as demand grows so you can serve more users, transactions and data. High-Scale TransactionsClustrix delivers high transactional query throughput with near linear scale at virtually any data set size and concurrency for all real-world query workloads.Real-time AnalyticsYou can run analytic queries against your main database (while running transactions) to get real-time insights and operational intelligence. Clustrix uses Massively Parallel Processing (MPP) that uses multiple cores across nodes in parallel to speed up your analytic queries.SQL, MySQL and ACIDWith Clustrix, you get ACID guarantees and the full power of a SQL interface. Our database is on the wire compatible with MySQL, which means that you can use your existing application code and connectors with Clustrix.Self-healingClustrix is easy to install and automates fault tolerance. Clustrix is built to be self-managing and simplifies operations allowing DBAs to focus on high value add tasks, greating reducing the ownership cost.Customer Proven Clustrix has been serving production workloads since 2008. We power dozens of large-scale production customers all around the world. Our largest customers have datasets with billions of rows, multiple terabytes of data, and non-trivial transactional workloads approaching 100,000 TPS in production.Superior ServiceClustrix provides services that out customers love. Our DBA-on-demand service provides deep technical insight. Managed services in DBaaS monitors your database to find issues before you do.
  2. Clustrix is built for applications with large data sets, growing customers/transactions and billions of rows. It is proven globally in production with more than 30 customers worldwide. Use this to drive home that our solution is proven in production in the real world, and that big names have bet on us (CSC, AOL, Rakuten, Symantec, etc.)Key points to emphasizeClustrix is proven in production at more than 30 customers around the world, like CSC, Symantec, AOL, and RakutenClustrix has reinvented the database from the ground up to deliver a scale-out SQL database platformKey takeawaysOther new database companies are in Beta or are being used in side-projectsClustrix is proven in production, and every customer is a reference.
  3. Customers, Reviews, Orders goes to NewSqlProducts goes to NoSQL documentStoring all in document meansOrder will contain copy of customer/productMultiple trips to the database with join in application