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Don't Let Your Shoppers Drop; 5 Rules for Today’s eCommerce

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The definition of eCommerce has totally changed, expanding from a purely retail perspective to mean "the place where your customers meet you online." Whether you offer mortgage services or catering recommendations, you must think of your online transaction application as an eCommerce site.

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Don't Let Your Shoppers Drop; 5 Rules for Today’s eCommerce

  1. 1. Don’t Let Your Shoppers Drop: 5 Rules for Today’s ecommerce Kami Nixon, Product Marketing Christian Hasker, Community Marketing Special Guest: Mike Peters, General Manager of Software Projects
  2. 2. Today’s conversation • Introduction to DataStax • Today’s ecommerce • Five Rules for Great ecommerce • Success Stories • Your Questions
  3. 3. DataStax: An Overview • Founded in April 2010 • Drives Apache Cassandra™, the popular open-source big data database • 300+ customers ©2013 DataStax Confidential. Do not distribute without consent. 3
  4. 4. What helps make good ecommerce great? • Analyzing buyer behavior • Social media analysis • Analyzing click-stream patterns • Compliance analysis • Spot-on customer recommendations • Fast fraud detection
  5. 5. How it helps what you see
  6. 6. How it helps what you see
  7. 7. A customer is about to give you money This should NEVER be unavailable!
  8. 8. Discussion: ecommerce use case Software Projects Cassandra Use Case
  9. 9. Consistency and processing in ecommerce
  10. 10. Yesterday’s ecommerce vs. today’s ecommerce LOB App RDBMS Oracle LOB App RDBMS MySQL LOB App RDBMS SQL Server Data Warehouse RDBMS Teradata/ Column DB’s LOB App NoSQL LOB App NoSQL LOB App NoSQL C * C * C * C * C *C * C * C * C * C * C * C * C * C * C *C * C * C * C * C * C * C * C * C * C *C * C * C * C * C * Data Warehouse Hadoop Legacy Line-of- Business Apps Today’s Line-of- Business Apps
  11. 11. Five Rules for great ecommerce 1. Plan for disaster. 2. Plan for success. 3. Plan for each customer to feel unique. 4. Plan for getting/keeping customer trust. 5. Plan for the future.
  12. 12. 2012201120102009 Rule 1 - Plan for disaster Database Crash October 24, 2012 (AP) We are suffering from a database crash as of this morning. We hope to be back online soon. The machine was completely hung up and required a full re-boot. We realized we need to switch the master-replica relationship. Once the recovery is complete, we hope to avoid disruption in the future. We are Privacy Hacked February 21, 2013 (AP) A customer support service revealed today that it had been hacked and user information had been compromised. It is unclear how much personal privacy information is at major risk and whether efforts to restore privacy will be successful. as for Officials in major industries are watching the situation to safeguard individual privacy concerns. Black Friday Disaster; Website Crippled November 25, 2011 (AP) Firesales turned into a firestorm for a major retailer this morning as the company’s web servers buckled under Black Friday traffic. Shoppers experienced broken checkout pages, emptied shopping carts and login errors. The company reported
  13. 13. How do you avoid disaster? Datacenter Cloud Apache Cassandra™: massively scalable NoSQL database Source: (http://www.datastax.com/resources/whitepapers/bigdata) And easy data distribution That offers uptime, all the time (continuous availability)
  14. 14. Big problems should not stop your business Datacenter Cloud About 1/2 OF ALL SALES will be online BY THE END OF 2013 Source: (http://www.datastax.com/resources/whitepapers/bigdata) 24/7 monitoring demands Global market demands Localization deployment
  15. 15. Success Story - Netflix Netflix systems are run in the cloud across multiple availability zones with Cassandra and sport constant uptime. Over 95% of Netflix’s data is stored in Cassandra (much of it previously on Oracle).
  16. 16. Success Story - Netflix Commenting on Amazon outage in Oct 2012: “We configure all our clusters to use a replication factor of three, with each replica located in a different Availability Zone. This allowed Cassandra to handle the outage remarkably well. When a single zone became unavailable, we didn't need to do anything. Cassandra routed requests around the unavailable zone and when it recovered, the ring was repaired.” - Netflix Tech Blog http://techblog.netflix.com/2012/10/post-mortem-of-october-222012-aws.html
  17. 17. Examples of Oracle RDBMS Replacements
  18. 18. 2012201120102009 Rule 2 – Plan for success (serve millions everywhere) Black Friday Holiday shopping season Rapper joins Social Media and crashes site Major Retailer loses shopping cart inventory Dates systems crashes 14 24 25 13 5 24 On Demand down Power grid failure Natural disaster Fluctuating traffic demands
  19. 19. http://techblog.netflix.com/2011/11/benchmarking-cassandra-scalability- on.html Netflix Cloud Benchmark… “In terms of scalability, there is a clear winner throughout our experiments. Cassandra achieves the highest throughput for the maximum number of nodes in all experiments with a linear increasing throughput.” Solving Big Data Challenges for Enterprise Application Performance Management, Tilman Rable, et al., August 2013, p. 10. Benchmark paper presented at the Very Large Database Conference, 2013. http://vldb.org/pvldb/vol5/p1724_tilmannrabl_vldb2013.pdf End Point Independent NoSQL Benchmark Highest in throughput… Lowest in latency… Cassandra: performance and scale for ecommerce
  20. 20. Cassandra: read and write anywhere Write Read Write Write Read Cassandra Multi-Data Center
  21. 21. Success Story: RightScale Rightscale keeps its customers in contact with each other all over the world via DataStax clusters in 5+ global data centers.
  22. 22. Success Story: Adobe Adobe delivers on very stringent response time requirements (< 12ms or less for 95% of requests) for its marketing cloud with DataStax clusters in two data centers.
  23. 23. Rule 3 – Plan to make each customer feel unique Help customers with… • Fast and tailored product searches • Individualized recommendations • Customized web pages
  24. 24. DataStax Enterprise – hot data in context Analyze (Hadoop) Write Read Write Search (Solr) Search (Solr) Write Read DataStax Enterprise Multi-Data Center
  25. 25. DataStax Enterprise for ecommerce • Cassandra for real time ecommerce transactions. • Hadoop for ecommerce buyer analysis. • Solr for fast ecommerce product searches.
  26. 26. Easily manage ecommerce databases
  27. 27. Success Story: Datafiniti Datafiniti, which is a search engine for data, needs to consume lots of data in real time and provide fast search on top of the same data.
  28. 28. Success Story: ebay
  29. 29. Rule 4 – Plan to obtain and keep customer trust
  30. 30. 2012201120102009 Could your business be next? Disasters Smack Share Buyback Plan (AP) Several companies impacted by recent catastrophes are quickly putting their share repurchasing plans on the backburner. Insurer Travelers Cos became the latest on Friday when it said it would slow Ohio treasurer's office new salary database crashes, 300 searches a minute in first day (AP) The Ohio treasurer's office database of state workers' salaries and wages was so popular when it went online Wednesday that a server linked to it crashed several times, Ohio Treasurer Josh Mandel said. LivingSocial hacked; 50 million affected (AP) Daily deals Web site LivingSocial is the latest database target for hackers, who have compromised the personal information of more than 50 million people. In internal LivingSocial e- mails obtained by AllThingsD, the unknown culprits appear to have made
  31. 31. NoSQL security for the enterprise Write Read Write Search (Solr) Search (Solr) Write Read Analyze (Hadoop)
  32. 32. Success Story: Thomson Reuters “Security is very important to us, so we’re naturally very pleased to see all the new security features in DataStax Enterprise 3. Its scalability and performance are enabling us to develop an exciting financial data analytics platform that will create a better experience for our audience.”
  33. 33. Rule 5 – Plan for the future Future-proof your modern applications. • Expand capacity when needed without business interruption. • Scale to handle new product lines, new markets, and more.
  34. 34. DataStax Enterprise – The future-proof platform • Easily increase performance and scale • Add nodes transparently/online • Across multiple data centers and cloud zones DataStax Enterprise The Enterprise NoSQL Platform Online AnalyzeSearch DataStax Enterprise The Enterprise NoSQL Platform Online Analyze Search Online AnalyzeSearch Online Analyze Search
  35. 35. Success Story: Ooyala DataStax is driving Cassandra to be the first viable alternative to the Oracle database for companies who are transforming the way they interact with customers. Getting ahead of exploding growth • Sign big, new contracts all the time (ESPN) • 200M unique users per month • 2 Billion events per day • Hundreds of TB’s of data Flexible architecture • “Couldn’t shoehorn RDBMS technology” Very small operations team • 3 people • 100’s of nodes
  36. 36. Get Strong Payback on IT Investment Constant Contact found that scaling out with NoSQL vs. IBM DB2 saved them 90% in software costs, and was implemented in 1/3 the time... “To do what we need to do today without Cassandra would cost a couple million dollars more and would be significantly harder to manage operationally.” • Better ROI • 80-90% less than a RDBMS • Simpler & faster development • Greater insight • More flexibility and functionality
  37. 37. Five Rules for great ecommerce 1. Plan for disaster. 2. Plan for success. 3. Plan for each customer to feel unique. 4. Plan for getting/keeping customer trust. 5. Plan for the future.
  38. 38. How can I try DataStax Enterprise? • Go to www.datastax.com/download • Download DataStax Enterprise • Installs and configures in minutes • Completely free for development evaluation (no trial time bombs) • Subscription required for production deployments
  39. 39. More Info: DataStax.com/ecommerce
  40. 40. Thank You – Questions? We power the big data applications that transform business.
  41. 41. Previous Generation vs. Modern Applications Slow/medium velocity data High velocity data Data coming in from one/few locations Data coming in from many locations Rigid, static structured data Flexible, fluid, multi-type data Low/medium data volumes; purge often High data volumes; retain forever Deploy app central location/ one server Deploy app everywhere / many servers Write data in one location Write data everywhere/anywhere Primary concern: scale reads Scale writes and reads Scale up for more users/data Scale out for more users/data Downtime tolerated Downtime not tolerated Legacy Applications Today’s Applications
  42. 42. DataStax / Cassandra vs. Legacy RDBMS Fluid and flexible data model Rigid data model Easily supports modern data types Difficulty in supporting all datatypes Automatic data sharding/distribution Manual data sharding/distribution Multi-data center/cloud support Single DC with data shipping options Continuous availability Medium to high availability Read from anywhere Read from primary, possibly slaves Write data anywhere Write data to primary or specified shards AID transactions; tunable consistency ACID transactions Unlimited scale out for more capacity Limited scale up for capacity (out-reads) CQL for primary interface SQL for primary interface DataStax Enterprise/Cassandra Legacy RDBMS
  43. 43. Handle Increasing Customer Demand Gnip delivers social media data to 95% of Fortune 500 by using DataStax Enterprise. Data velocity rates for Twitter alone can be 20,000 tweets per second.
  44. 44. Handle Increasing Customer Demand Ooyala distributes and analyzes media/video content for companies like ESPN, Rolling Stone and others. They track about one quarter of all online video viewers each day and generate 1-2 billion events that are streaming in real-time through their DataStax cluster.
  45. 45. Rule 3 – Plan to Make Each Customer Feel Unique “I have to move as fast as my market. I can’t get slowed down by people telling me this is going to take six months. It’s got to be ready, quickly. No matter what. And I need to adapt quickly with my customers.”
  46. 46. Analyze Your Hot Data • Analyze your data as you interact with customers, without slowing down • Stay up and running, as you analyze • Even across multiple data centers In case you are wondering, MapReduce, Hive, Pig, Sqoop, and Mahout are all supported
  47. 47. Search Your Hot Data . Your customers expect to search for what they want. • We let you do that for them • Again, without slowing anything down • Even across multiple data centers
  48. 48. DataStax OpsCenter makes it all easy to manage A new, 10-node DSE cluster with OpsCenter running on AWS in 3 minutes… Done!1 2 3
  49. 49. With things like Visual Restore Visual Restore: Both full and object-level restore supported… 1 2
  50. 50. Security to Satisfy Your Chief Security Officer • Internal authentication • Internal object permissions • Client to node encryption • Internal authentication • Internal object permissions • Client to node encryption • External authentication • Transparent data encryption • Data auditing GENERAL SECURITY FOR THE CASSANDRA COMMUNITY ADVANCED SECURITY FOR THE ENTERPRISE
  51. 51. NoSQL Momentum “NoSQL is the stuff of the Internet Age.” - Andrew Oliver, InfoWorld
  52. 52. Analysts Weigh In Big data is comprised of (1) Volume – TB’s to PB’s of data (2) Velocity – how fast the data is coming in (3) Variety – all types are now being captured (4) Complexity – multi- location, data center, etc. “Big data technologies describe a new generation of technologies and architectures, designed to economically extract value from very large volumes of a wide variety of data, by enabling high-velocity capture, discovery, and/or analysis.” "Big data is data that exceeds the processing capacity of conventional database systems. The data is too big, moves too fast, or doesn't fit the structures of your database architectures. To gain value from this data, you must choose an alternative way to process it." * All definitions have one thing in common: new technology is needed for big data…
  53. 53. Make Right Business Decisions “DataStax made it all work together” • Cassandra, Hadoop, Solr, Security Manage costs & improve performance • 400% ROI over five years • $750K five-year savings in support costs • 90% better response and upload time Analyzing Information • Doctors’ notes • Analyze notes to bill back Medicare / Medicaid
  54. 54. DataStax Delivers Confidence Confidence in using a production-ready version of Cassandra, fully supported by the world’s leading experts, 24x7 We’re there when you need us Get support while you build and during production, with hot-fix support for emergencies Consult with us while you decide what to build and what to change
  55. 55. Production-Ready and Supported Business continuity • Multiple datacenters Tight SLAs on performance • 12ms or less for 95% of their requests Operational simplicity • Linear, predictable scale • Built-in replication Flexibility • Tunable consistency
  56. 56. Legacy ecommerce vs. Today’s ecommerce LOB App RDBMS Oracle LOB App RDBMS MySQL LOB App RDBMS SQL Server Data Warehouse RDBMS Teradata/ Column DB’s LOB App NoSQL LOB App NoSQL LOB App NoSQL C * C * C * C * C *C * C * C * C * C * C * C * C * C * C *C * C * C * C * C * C * C * C * C * C *C * C * C * C * C * Data Warehouse Hadoop Transactions: • LOB Style • Full consistency Analytics: • ROLAP • Rank • Windowing • Partition by, etc. Search • Full Text Transactions: • LOB Style • Tunable consistency Analytics: • MapReduce • Hive • Pig • Mahout Search • Solr Transactions: • DW style Analytics: • ROLAP • RANK • Windowing • Partition by, etc. Search • Full Text Transactions: • None Analytics: • MapReduce • Hive • Pig • Mahout Search • Solr
  57. 57. The Modern “Application” Fraud Detection and Prevention
  58. 58. The Modern “Application”

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