Big Data Paris : Hadoop and NoSQL
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Big Data Paris : Hadoop and NoSQL

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Quick overview of the benefits and some use case of BigD

Quick overview of the benefits and some use case of BigD

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  • The database industry is about $30B today and is dominated by companies like Oracle, IBM, and Microsoft Relational technology has dominated the industry for the last 40 years and is the technology underpinning for 95% of the industry today. We believe the database industry is being disrupted. In 10 – 15 years we believe relational technology will make up a much smaller percentage of the industry. It’s too early to tell whether it will be 50%, 40%, or 30% percent but it seems clear to me it will be much small than 95% We believe most of the future operational database growth will be NoSQL
  • There are two types of databases . Each is focused on a very different problem. Analytic databases were referred to in the past as OLAP databases. They are focused on looking through every record in a huge database to answer a question or gain an insight about the data contained in it. These analyses are batch processes that access every piece of data in the database, are very “ read ” heavy, and produce results in seconds , minutes, or sometimes days . For analytic databases, “real time” means an analysis takes a few seconds to run. Real-time interactive databases are often referred to as operational databases. They store a lot of data but usually much less than an analytic database. They must provide access to individual records in a database in milliseconds so that users of an application get good response time. Since the requirements of each database is very different, the architectures and capabilities of each are very different as well. When I refer to NoSQL in my presentation , I am referring to real-time, interactive databases . This is the type of NoSQL database Couchbase provides.

Big Data Paris : Hadoop and NoSQL Big Data Paris : Hadoop and NoSQL Presentation Transcript

  • BigData - NoSQLHadoop - CouchbaseHadoop - Couchbase Tugdual “Tug” Grall Technical Evangelist
  • About Me• Tugdual “Tug” Grall • Web ­ Couchbase • @tgrall • Technical Evangelist • http://blog.grallandco.com ­ eXo • CTO • tgrallNantesJUG co- ­ Oracle founderPet Project :http://www.resultri.com • Developer/Product Manager • Mainly Java/SOA • http://www.resultri.com ­ Developer in consulting firms • http://www.resultri.com http://www.resultri.com
  • $30B Database Market Being Disrupted95% <50%? Relational RelationalTechnology Other Technology Relational Technology Relational NoSQL Technology Technology 2012 2027 All new database growth will be NoSQL All new database growth will be NoSQL
  • Operational vs. Analytic Databases Real-time, Analytic Interactive Databases Databases NoSQL Fast access Get insights from to data data Couchbase Cassandra Cloudera MongoDB Hbase Hortonworks Mapr
  • 49% 35% 29% 16% 12% 11% Lack of flexibility/ Inability to scale Performance Cost All of these Other rigid schemas out data challengesSource: Couchbase Survey, December 2011, n = 1351.
  • Hadoop and NoSQL
  • What is Sqoop?Sqoop is a tool designed to transfer data between Hadoop and relationaldatabases.You can use Sqoop to import data from a relational database managementsystem (RDBMS) such as MySQL or Oracle into the Hadoop Distributed FileSystem (HDFS), transform the data in Hadoop MapReduce, and then exportthe data back into an RDBMS. sqoop.apache.org
  • What is Sqoop?• Traditional ETLTraditional ETL T Data Application Data
  • What is Sqoop?• A different paradigmA different paradigm Applicatio n Data Data
  • • A very scalable different paradigmA very scalable different paradigm Application Data Application Data Application Data Data
  • What is Sqoop?• Where did the Transform go?Where did the Transform go? TTT TTT TTT TTT Applicatio n Data
  • What is Sqoop?• Sqoop• Default connection is via JDBCLots of custom connectorsCouchbase, VoltDB, VerticaTeradata, NetezzaOracle, MySQL, Postgres • Couchbase, VoltDB, VerticaTeradata, NetezzaOracle, MySQL, Postgres
  • Ad and offer targeting 40 milliseconds to respond with the decision. profiles, real time campaign 3 statistics 2 1 profiles, campaigns events
  • Moving Parts
  • Content & Recommendation Targeting
  • Moving Parts
  • Couchbase
  • Couchbase Server Core Principles Easy Consistent High Scalability Performance Grow cluster without application Consistent sub-millisecond changes, without downtime with a read and write response times single click with consistent high throughput Always On Flexible Data 24x365 Model No downtime for software JSON document model with noupgrades, hardware maintenance, fixed schema. etc.
  • Couchbase Handles Real World Scale
  • Q&A