The evolution of database technology (II) Huibert Aalbers Senior Certified Executive IT Architect

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "The evolution of database technology (II) Huibert Aalbers Senior Certified Executive IT Architect"

Transcription

1 The evolution of database technology (II) Huibert Aalbers Senior Certified Executive IT Architect

2 IT Insight podcast This podcast belongs to the IT Insight series You can subscribe to the podcast through itunes. Additional material such as presentations in PDF format or white papers mentioned in the podcast can be downloaded from the IT insight section of my site at You can send questions or suggestions regarding this podcast to my personal ,

3 A brave new world With Web 2.0, came the need for a new set of tools that could handle an explosive growth of data Data willfully shared by the users Data collected on users and customers, sometimes unsuspectedly on their part Sensors, IoT, etc. Big Data requires a new kind of data repository

4 Do I need a different solution? There are basically two ways to determine that you require a new type of database solution instead of a traditional relational database The architect designs a new system from the ground up using a Big Data solution because he knowns that it will require it The team has tried every single strategy to try to scale the existing relational database and it is still not enough Upgrading the hardware / use of SSDs / Networking, etc. Query optimization Using a data caching scheme Partitioning the data Building new indices Denormalizing the data Using stored procedures, etc.

5 In order to solve the issue, we have to give up something What can we give up? ACID properties Data normalization Transaction support

6 No SQL Repositories From my point of view, the name No SQL is not right to describe non-relational databases The success behind No SQL databases is not related to the fact that developers don t like SQL. It is due to the following reasons: They scale linearly They are more flexible (schema-less) Easier to manage for extremely high volumes of data I think it is better to call them distributed nonrelational databases

7 Key-Value pair databases These data stores are also known as distributed hash tables Pros Extremely quick, well understood CS problem Scale almost linearly Cons Performing complex queries against the values can be slow and complex Key-value pair data stores in which the product also keeps a time stamp on the data for versioning are a particular case of key-value pair databases

8 Document based databases This is a large category of data stores which allow to work with data stored in a particular document format. Among popular document formats used to store data, we could mention: XML JSON YAML In this kind of data stores, documents are identified by a unique key, which allows for quick retrieval of the information. Although conceptually all data stores in this category are relatively similar, there are still important differences from one product to another Query methods (SQL like, Map/Reduce, etc.) Replication Data consistency Document based databases are schema-less

9 MongoDB vs CouchDB MongoDB Very high volumes of data somewhat mutable data Dynamic flexible queries, somewhat similar to SQL Very quick queries CouchDB Very high volumes of mostly immutable data Pre-defined queries, based on MapReduce, implemented in Javascript Master-Master replication Neither MongoDB nor CouchDB natively work with XML data, both work with JSON documents

10 Document based databases Among the many Document based databases, MongoDB is currently the most popular, closely followed by CouchDB The MongoDB API is currently supported by both DB2 and Informix That means that it is now very easy to migrate from mongodb to any of those databases and store in a single repository both structured data and JSON documents

11 Hosted Document databases Both MongoDB and CouchDB are popular databases, which explains why there are many options to use both hosted and managed versions of these products Cloudant is a fully managed version of BigCouch, which is in turn a high availability, fault tolerant version of CouchDB Migrating from CouchDB or BigCouch to Cloudant is totally transparent Both MongoDB and CouchDB scale very well by implementing sharding, which make them very well suited for born-on-cloud applications

12 Graph databases Social networks have become one of the most representative applications of what is known as Web 2.0 Storing and processing social graphs in relational is both complex and inefficient Unlike relational databases, this new kind of data stores focuses more on relationships than on data. For social networks kind of projects this results in: Increased performance Simpler and more natural development

13 Hadoop Hadoop is a framework designed to process tasks that can be parallelized on extremely high volumes of data distributed over a large number of server nodes belonging to a cluster. It has four main components: Hadoop common Hadoop Distributed File System (HDFS) Designed primarily to handle extremely high volumes of immutable data Loading and deleting data is efficient, updating data is not Hadoop YARN Hadoop MapReduce Managing a complete Hadoop system is currently not for the faint of heart

14 MapReduce MapReduce is the data processing algorithm that sits at the very core of Hadoop Developers need to implement for each query the following functions: Map: In this phase the overall problem is divided into smaller problems which can be divided into smaller tasks (which can also be further broken down) that can be distributed to run on different server nodes Reduce: In this second phase, the master node combines the answers received from the different nodes and processes them to produce a reply to the query

15 MapReduce Hadoop allows to store any kind of data Structured Unstructured When using Hadoop to store structured data, in a data warehouse like environment, it is possible to use languages that automatically generate the code for the Map/Reduce functions Apache Pig (pig latin) Apache Hive (HiveQL, similar to SQL) IBM Big SQL

16 Analyzing streams of data Sometimes the amount of stored data is so large that it simply becomes impossible to perform real time analysis In those cases, the best alternative is to analyze the stream of data before it is stored in the database The main idea is that the data is kept outside the database (generally in RAM) during a certain window of time in order to detect a combination of events in a short period of time Fraud detection Digital marketing

17 Polygot Persistence When working with applications that require extreme scaling, there is no solution that fits all challenges. It is likely that after careful analysis of the problem more than one datastore will be required to obtain the best performance. This is known as Polygot Persistence

18 Contact information On (Spanish) Web site: Blog:

Cloud Scale Distributed Data Storage. Jürmo Mehine

Cloud Scale Distributed Data Storage. Jürmo Mehine Cloud Scale Distributed Data Storage Jürmo Mehine 2014 Outline Background Relational model Database scaling Keys, values and aggregates The NoSQL landscape Non-relational data models Key-value Document-oriented

More information

Hadoop. MPDL-Frühstück 9. Dezember 2013 MPDL INTERN

Hadoop. MPDL-Frühstück 9. Dezember 2013 MPDL INTERN Hadoop MPDL-Frühstück 9. Dezember 2013 MPDL INTERN Understanding Hadoop Understanding Hadoop What's Hadoop about? Apache Hadoop project (started 2008) downloadable open-source software library (current

More information

SQL VS. NO-SQL. Adapted Slides from Dr. Jennifer Widom from Stanford

SQL VS. NO-SQL. Adapted Slides from Dr. Jennifer Widom from Stanford SQL VS. NO-SQL Adapted Slides from Dr. Jennifer Widom from Stanford 55 Traditional Databases SQL = Traditional relational DBMS Hugely popular among data analysts Widely adopted for transaction systems

More information

Introduction to Hadoop. New York Oracle User Group Vikas Sawhney

Introduction to Hadoop. New York Oracle User Group Vikas Sawhney Introduction to Hadoop New York Oracle User Group Vikas Sawhney GENERAL AGENDA Driving Factors behind BIG-DATA NOSQL Database 2014 Database Landscape Hadoop Architecture Map/Reduce Hadoop Eco-system Hadoop

More information

Analytics March 2015 White paper. Why NoSQL? Your database options in the new non-relational world

Analytics March 2015 White paper. Why NoSQL? Your database options in the new non-relational world Analytics March 2015 White paper Why NoSQL? Your database options in the new non-relational world 2 Why NoSQL? Contents 2 New types of apps are generating new types of data 2 A brief history of NoSQL 3

More information

In Memory Accelerator for MongoDB

In Memory Accelerator for MongoDB In Memory Accelerator for MongoDB Yakov Zhdanov, Director R&D GridGain Systems GridGain: In Memory Computing Leader 5 years in production 100s of customers & users Starts every 10 secs worldwide Over 15,000,000

More information

Why NoSQL? Your database options in the new non- relational world. 2015 IBM Cloudant 1

Why NoSQL? Your database options in the new non- relational world. 2015 IBM Cloudant 1 Why NoSQL? Your database options in the new non- relational world 2015 IBM Cloudant 1 Table of Contents New types of apps are generating new types of data... 3 A brief history on NoSQL... 3 NoSQL s roots

More information

WINDOWS AZURE DATA MANAGEMENT AND BUSINESS ANALYTICS

WINDOWS AZURE DATA MANAGEMENT AND BUSINESS ANALYTICS WINDOWS AZURE DATA MANAGEMENT AND BUSINESS ANALYTICS Managing and analyzing data in the cloud is just as important as it is anywhere else. To let you do this, Windows Azure provides a range of technologies

More information

extensible record stores document stores key-value stores Rick Cattel s clustering from Scalable SQL and NoSQL Data Stores SIGMOD Record, 2010

extensible record stores document stores key-value stores Rick Cattel s clustering from Scalable SQL and NoSQL Data Stores SIGMOD Record, 2010 System/ Scale to Primary Secondary Joins/ Integrity Language/ Data Year Paper 1000s Index Indexes Transactions Analytics Constraints Views Algebra model my label 1971 RDBMS O tables sql-like 2003 memcached

More information

Big Data Course Highlights

Big Data Course Highlights Big Data Course Highlights The Big Data course will start with the basics of Linux which are required to get started with Big Data and then slowly progress from some of the basics of Hadoop/Big Data (like

More information

Challenges for Data Driven Systems

Challenges for Data Driven Systems Challenges for Data Driven Systems Eiko Yoneki University of Cambridge Computer Laboratory Quick History of Data Management 4000 B C Manual recording From tablets to papyrus to paper A. Payberah 2014 2

More information

Understanding NoSQL Technologies on Windows Azure

Understanding NoSQL Technologies on Windows Azure David Chappell Understanding NoSQL Technologies on Windows Azure Sponsored by Microsoft Corporation Copyright 2013 Chappell & Associates Contents Data on Windows Azure: The Big Picture... 3 Windows Azure

More information

Firebird meets NoSQL (Apache HBase) Case Study

Firebird meets NoSQL (Apache HBase) Case Study Firebird meets NoSQL (Apache HBase) Case Study Firebird Conference 2011 Luxembourg 25.11.2011 26.11.2011 Thomas Steinmaurer DI +43 7236 3343 896 thomas.steinmaurer@scch.at www.scch.at Michael Zwick DI

More information

An Approach to Implement Map Reduce with NoSQL Databases

An Approach to Implement Map Reduce with NoSQL Databases www.ijecs.in International Journal Of Engineering And Computer Science ISSN: 2319-7242 Volume 4 Issue 8 Aug 2015, Page No. 13635-13639 An Approach to Implement Map Reduce with NoSQL Databases Ashutosh

More information

NoSQL Data Base Basics

NoSQL Data Base Basics NoSQL Data Base Basics Course Notes in Transparency Format Cloud Computing MIRI (CLC-MIRI) UPC Master in Innovation & Research in Informatics Spring- 2013 Jordi Torres, UPC - BSC www.jorditorres.eu HDFS

More information

Open Source Technologies on Microsoft Azure

Open Source Technologies on Microsoft Azure Open Source Technologies on Microsoft Azure A Survey @DChappellAssoc Copyright 2014 Chappell & Associates The Main Idea i Open source technologies are a fundamental part of Microsoft Azure The Big Questions

More information

Big Data Management. Big Data Management. (BDM) Autumn 2013. Povl Koch September 30, 2013 29-09-2013 1

Big Data Management. Big Data Management. (BDM) Autumn 2013. Povl Koch September 30, 2013 29-09-2013 1 Big Data Management Big Data Management (BDM) Autumn 2013 Povl Koch September 30, 2013 29-09-2013 1 Overview Today s program 1. Little more practical details about this course 2. Recap from last time 3.

More information

HadoopRDF : A Scalable RDF Data Analysis System

HadoopRDF : A Scalable RDF Data Analysis System HadoopRDF : A Scalable RDF Data Analysis System Yuan Tian 1, Jinhang DU 1, Haofen Wang 1, Yuan Ni 2, and Yong Yu 1 1 Shanghai Jiao Tong University, Shanghai, China {tian,dujh,whfcarter}@apex.sjtu.edu.cn

More information

Implement Hadoop jobs to extract business value from large and varied data sets

Implement Hadoop jobs to extract business value from large and varied data sets Hadoop Development for Big Data Solutions: Hands-On You Will Learn How To: Implement Hadoop jobs to extract business value from large and varied data sets Write, customize and deploy MapReduce jobs to

More information

III Big Data Technologies

III Big Data Technologies III Big Data Technologies Today, new technologies make it possible to realize value from Big Data. Big data technologies can replace highly customized, expensive legacy systems with a standard solution

More information

INTERNATIONAL JOURNAL OF PURE AND APPLIED RESEARCH IN ENGINEERING AND TECHNOLOGY

INTERNATIONAL JOURNAL OF PURE AND APPLIED RESEARCH IN ENGINEERING AND TECHNOLOGY INTERNATIONAL JOURNAL OF PURE AND APPLIED RESEARCH IN ENGINEERING AND TECHNOLOGY A PATH FOR HORIZING YOUR INNOVATIVE WORK OVERVIEW ON BIG DATA SYSTEMATIC TOOLS MR. SACHIN D. CHAVHAN 1, PROF. S. A. BHURA

More information

Can the Elephants Handle the NoSQL Onslaught?

Can the Elephants Handle the NoSQL Onslaught? Can the Elephants Handle the NoSQL Onslaught? Avrilia Floratou, Nikhil Teletia David J. DeWitt, Jignesh M. Patel, Donghui Zhang University of Wisconsin-Madison Microsoft Jim Gray Systems Lab Presented

More information

ON-LINE VIDEO ANALYTICS EMBRACING BIG DATA

ON-LINE VIDEO ANALYTICS EMBRACING BIG DATA ON-LINE VIDEO ANALYTICS EMBRACING BIG DATA David Vanderfeesten, Bell Labs Belgium ANNO 2012 YOUR DATA IS MONEY BIG MONEY! Your click stream, your activity stream, your electricity consumption, your call

More information

A survey of big data architectures for handling massive data

A survey of big data architectures for handling massive data CSIT 6910 Independent Project A survey of big data architectures for handling massive data Jordy Domingos - jordydomingos@gmail.com Supervisor : Dr David Rossiter Content Table 1 - Introduction a - Context

More information

Lambda Architecture. Near Real-Time Big Data Analytics Using Hadoop. January 2015. Email: bdg@qburst.com Website: www.qburst.com

Lambda Architecture. Near Real-Time Big Data Analytics Using Hadoop. January 2015. Email: bdg@qburst.com Website: www.qburst.com Lambda Architecture Near Real-Time Big Data Analytics Using Hadoop January 2015 Contents Overview... 3 Lambda Architecture: A Quick Introduction... 4 Batch Layer... 4 Serving Layer... 4 Speed Layer...

More information

NoSQL Database Options

NoSQL Database Options NoSQL Database Options Introduction For this report, I chose to look at MongoDB, Cassandra, and Riak. I chose MongoDB because it is quite commonly used in the industry. I chose Cassandra because it has

More information

Big Data Management. Big Data Management. (BDM) Autumn 2013. Povl Koch September 16, 2013 15-09-2013 1

Big Data Management. Big Data Management. (BDM) Autumn 2013. Povl Koch September 16, 2013 15-09-2013 1 Big Data Management Big Data Management (BDM) Autumn 2013 Povl Koch September 16, 2013 15-09-2013 1 Overview Today s program 1. Little more practical details about this course 2. Chapter 7 in NoSQL Distilled

More information

Lecture Data Warehouse Systems

Lecture Data Warehouse Systems Lecture Data Warehouse Systems Eva Zangerle SS 2013 PART C: Novel Approaches in DW NoSQL and MapReduce Stonebraker on Data Warehouses Star and snowflake schemas are a good idea in the DW world C-Stores

More information

Big Systems, Big Data

Big Systems, Big Data Big Systems, Big Data When considering Big Distributed Systems, it can be noted that a major concern is dealing with data, and in particular, Big Data Have general data issues (such as latency, availability,

More information

TRAINING PROGRAM ON BIGDATA/HADOOP

TRAINING PROGRAM ON BIGDATA/HADOOP Course: Training on Bigdata/Hadoop with Hands-on Course Duration / Dates / Time: 4 Days / 24th - 27th June 2015 / 9:30-17:30 Hrs Venue: Eagle Photonics Pvt Ltd First Floor, Plot No 31, Sector 19C, Vashi,

More information

Speak Tech Brief. RichRelevance Distributed Computing: creating a scalable, reliable infrastructure

Speak<geek> Tech Brief. RichRelevance Distributed Computing: creating a scalable, reliable infrastructure 3 Speak Tech Brief RichRelevance Distributed Computing: creating a scalable, reliable infrastructure Overview Scaling a large database is not an overnight process, so it s difficult to plan and implement

More information

Understanding NoSQL on Microsoft Azure

Understanding NoSQL on Microsoft Azure David Chappell Understanding NoSQL on Microsoft Azure Sponsored by Microsoft Corporation Copyright 2014 Chappell & Associates Contents Data on Azure: The Big Picture... 3 Relational Technology: A Quick

More information

Making Sense ofnosql A GUIDE FOR MANAGERS AND THE REST OF US DAN MCCREARY MANNING ANN KELLY. Shelter Island

Making Sense ofnosql A GUIDE FOR MANAGERS AND THE REST OF US DAN MCCREARY MANNING ANN KELLY. Shelter Island Making Sense ofnosql A GUIDE FOR MANAGERS AND THE REST OF US DAN MCCREARY ANN KELLY II MANNING Shelter Island contents foreword preface xvii xix acknowledgments xxi about this book xxii Part 1 Introduction

More information

Hadoop and Map-Reduce. Swati Gore

Hadoop and Map-Reduce. Swati Gore Hadoop and Map-Reduce Swati Gore Contents Why Hadoop? Hadoop Overview Hadoop Architecture Working Description Fault Tolerance Limitations Why Map-Reduce not MPI Distributed sort Why Hadoop? Existing Data

More information

Applications for Big Data Analytics

Applications for Big Data Analytics Smarter Healthcare Applications for Big Data Analytics Multi-channel sales Finance Log Analysis Homeland Security Traffic Control Telecom Search Quality Manufacturing Trading Analytics Fraud and Risk Retail:

More information

Overview of Databases On MacOS. Karl Kuehn Automation Engineer RethinkDB

Overview of Databases On MacOS. Karl Kuehn Automation Engineer RethinkDB Overview of Databases On MacOS Karl Kuehn Automation Engineer RethinkDB Session Goals Introduce Database concepts Show example players Not Goals: Cover non-macos systems (Oracle) Teach you SQL Answer what

More information

A Brief Outline on Bigdata Hadoop

A Brief Outline on Bigdata Hadoop A Brief Outline on Bigdata Hadoop Twinkle Gupta 1, Shruti Dixit 2 RGPV, Department of Computer Science and Engineering, Acropolis Institute of Technology and Research, Indore, India Abstract- Bigdata is

More information

Apache Hadoop: The Big Data Refinery

Apache Hadoop: The Big Data Refinery Architecting the Future of Big Data Whitepaper Apache Hadoop: The Big Data Refinery Introduction Big data has become an extremely popular term, due to the well-documented explosion in the amount of data

More information

HDFS. Hadoop Distributed File System

HDFS. Hadoop Distributed File System HDFS Kevin Swingler Hadoop Distributed File System File system designed to store VERY large files Streaming data access Running across clusters of commodity hardware Resilient to node failure 1 Large files

More information

MapReduce with Apache Hadoop Analysing Big Data

MapReduce with Apache Hadoop Analysing Big Data MapReduce with Apache Hadoop Analysing Big Data April 2010 Gavin Heavyside gavin.heavyside@journeydynamics.com About Journey Dynamics Founded in 2006 to develop software technology to address the issues

More information

Integrating Big Data into the Computing Curricula

Integrating Big Data into the Computing Curricula Integrating Big Data into the Computing Curricula Yasin Silva, Suzanne Dietrich, Jason Reed, Lisa Tsosie Arizona State University http://www.public.asu.edu/~ynsilva/ibigdata/ 1 Overview Motivation Big

More information

Transforming the Telecoms Business using Big Data and Analytics

Transforming the Telecoms Business using Big Data and Analytics Transforming the Telecoms Business using Big Data and Analytics Event: ICT Forum for HR Professionals Venue: Meikles Hotel, Harare, Zimbabwe Date: 19 th 21 st August 2015 AFRALTI 1 Objectives Describe

More information

Sentimental Analysis using Hadoop Phase 2: Week 2

Sentimental Analysis using Hadoop Phase 2: Week 2 Sentimental Analysis using Hadoop Phase 2: Week 2 MARKET / INDUSTRY, FUTURE SCOPE BY ANKUR UPRIT The key value type basically, uses a hash table in which there exists a unique key and a pointer to a particular

More information

Brave New World: Hadoop vs. Spark

Brave New World: Hadoop vs. Spark Brave New World: Hadoop vs. Spark Dr. Kurt Stockinger Associate Professor of Computer Science Director of Studies in Data Science Zurich University of Applied Sciences Datalab Seminar, Zurich, Oct. 7,

More information

Comparison of the Frontier Distributed Database Caching System with NoSQL Databases

Comparison of the Frontier Distributed Database Caching System with NoSQL Databases Comparison of the Frontier Distributed Database Caching System with NoSQL Databases Dave Dykstra dwd@fnal.gov Fermilab is operated by the Fermi Research Alliance, LLC under contract No. DE-AC02-07CH11359

More information

Structured Data Storage

Structured Data Storage Structured Data Storage Xgen Congress Short Course 2010 Adam Kraut BioTeam Inc. Independent Consulting Shop: Vendor/technology agnostic Staffed by: Scientists forced to learn High Performance IT to conduct

More information

So What s the Big Deal?

So What s the Big Deal? So What s the Big Deal? Presentation Agenda Introduction What is Big Data? So What is the Big Deal? Big Data Technologies Identifying Big Data Opportunities Conducting a Big Data Proof of Concept Big Data

More information

MongoDB in the NoSQL and SQL world. Horst Rechner horst.rechner@fokus.fraunhofer.de Berlin, 2012-05-15

MongoDB in the NoSQL and SQL world. Horst Rechner horst.rechner@fokus.fraunhofer.de Berlin, 2012-05-15 MongoDB in the NoSQL and SQL world. Horst Rechner horst.rechner@fokus.fraunhofer.de Berlin, 2012-05-15 1 MongoDB in the NoSQL and SQL world. NoSQL What? Why? - How? Say goodbye to ACID, hello BASE You

More information

NoSQL for SQL Professionals William McKnight

NoSQL for SQL Professionals William McKnight NoSQL for SQL Professionals William McKnight Session Code BD03 About your Speaker, William McKnight President, McKnight Consulting Group Frequent keynote speaker and trainer internationally Consulted to

More information

Lofan Abrams Data Services for Big Data Session # 2987

Lofan Abrams Data Services for Big Data Session # 2987 Lofan Abrams Data Services for Big Data Session # 2987 Big Data Are you ready for blast-off? Big Data, for better or worse: 90% of world s data generated over last two years. ScienceDaily, ScienceDaily

More information

Data Modeling for Big Data

Data Modeling for Big Data Data Modeling for Big Data by Jinbao Zhu, Principal Software Engineer, and Allen Wang, Manager, Software Engineering, CA Technologies In the Internet era, the volume of data we deal with has grown to terabytes

More information

Big Data. White Paper. Big Data Executive Overview WP-BD-10312014-01. Jafar Shunnar & Dan Raver. Page 1 Last Updated 11-10-2014

Big Data. White Paper. Big Data Executive Overview WP-BD-10312014-01. Jafar Shunnar & Dan Raver. Page 1 Last Updated 11-10-2014 White Paper Big Data Executive Overview WP-BD-10312014-01 By Jafar Shunnar & Dan Raver Page 1 Last Updated 11-10-2014 Table of Contents Section 01 Big Data Facts Page 3-4 Section 02 What is Big Data? Page

More information

Chapter 11 Map-Reduce, Hadoop, HDFS, Hbase, MongoDB, Apache HIVE, and Related

Chapter 11 Map-Reduce, Hadoop, HDFS, Hbase, MongoDB, Apache HIVE, and Related Chapter 11 Map-Reduce, Hadoop, HDFS, Hbase, MongoDB, Apache HIVE, and Related Summary Xiangzhe Li Nowadays, there are more and more data everyday about everything. For instance, here are some of the astonishing

More information

Alternatives to HIVE SQL in Hadoop File Structure

Alternatives to HIVE SQL in Hadoop File Structure Alternatives to HIVE SQL in Hadoop File Structure Ms. Arpana Chaturvedi, Ms. Poonam Verma ABSTRACT Trends face ups and lows.in the present scenario the social networking sites have been in the vogue. The

More information

X4-2 Exadata announced (well actually around Jan 1) OEM/Grid control 12c R4 just released

X4-2 Exadata announced (well actually around Jan 1) OEM/Grid control 12c R4 just released General announcements In-Memory is available next month http://www.oracle.com/us/corporate/events/dbim/index.html X4-2 Exadata announced (well actually around Jan 1) OEM/Grid control 12c R4 just released

More information

Introduction to Big Data Training

Introduction to Big Data Training Introduction to Big Data Training The quickest way to be introduce with NOSQL/BIG DATA offerings Learn and experience Big Data Solutions including Hadoop HDFS, Map Reduce, NoSQL DBs: Document Based DB

More information

Certified Apache CouchDB Professional VS-1045

Certified Apache CouchDB Professional VS-1045 Certified Apache CouchDB Professional VS-1045 Certified Apache CouchDB Professional Certification Code VS-1045 Vskills certification for Apache CouchDB Professional assesses the candidate for couchdb database.

More information

Big Data on Microsoft Platform

Big Data on Microsoft Platform Big Data on Microsoft Platform Prepared by GJ Srinivas Corporate TEG - Microsoft Page 1 Contents 1. What is Big Data?...3 2. Characteristics of Big Data...3 3. Enter Hadoop...3 4. Microsoft Big Data Solutions...4

More information

DROSS Distributed & Resilient Open Source Software

DROSS Distributed & Resilient Open Source Software DROSS Distributed & Resilient Open Source Software Andrew Hardie http://ashardie.com ECPRD WGICT 17-21 November 2010 Chamber of Deputies, Bucharest 17-21 November 2010 ECPRD - WGICT - Bucharest 1 Topics

More information

Big Data and Apache Hadoop s MapReduce

Big Data and Apache Hadoop s MapReduce Big Data and Apache Hadoop s MapReduce Michael Hahsler Computer Science and Engineering Southern Methodist University January 23, 2012 Michael Hahsler (SMU/CSE) Hadoop/MapReduce January 23, 2012 1 / 23

More information

Real Time Fraud Detection With Sequence Mining on Big Data Platform. Pranab Ghosh Big Data Consultant IEEE CNSV meeting, May 6 2014 Santa Clara, CA

Real Time Fraud Detection With Sequence Mining on Big Data Platform. Pranab Ghosh Big Data Consultant IEEE CNSV meeting, May 6 2014 Santa Clara, CA Real Time Fraud Detection With Sequence Mining on Big Data Platform Pranab Ghosh Big Data Consultant IEEE CNSV meeting, May 6 2014 Santa Clara, CA Open Source Big Data Eco System Query (NOSQL) : Cassandra,

More information

ITG Software Engineering

ITG Software Engineering Introduction to Apache Hadoop Course ID: Page 1 Last Updated 12/15/2014 Introduction to Apache Hadoop Course Overview: This 5 day course introduces the student to the Hadoop architecture, file system,

More information

Microsoft Azure Data Technologies: An Overview

Microsoft Azure Data Technologies: An Overview David Chappell Microsoft Azure Data Technologies: An Overview Sponsored by Microsoft Corporation Copyright 2014 Chappell & Associates Contents Blobs... 3 Running a DBMS in a Virtual Machine... 4 SQL Database...

More information

Big Data Buzzwords From A to Z. By Rick Whiting, CRN 4:00 PM ET Wed. Nov. 28, 2012

Big Data Buzzwords From A to Z. By Rick Whiting, CRN 4:00 PM ET Wed. Nov. 28, 2012 Big Data Buzzwords From A to Z By Rick Whiting, CRN 4:00 PM ET Wed. Nov. 28, 2012 Big Data Buzzwords Big data is one of the, well, biggest trends in IT today, and it has spawned a whole new generation

More information

Hadoop Job Oriented Training Agenda

Hadoop Job Oriented Training Agenda 1 Hadoop Job Oriented Training Agenda Kapil CK hdpguru@gmail.com Module 1 M o d u l e 1 Understanding Hadoop This module covers an overview of big data, Hadoop, and the Hortonworks Data Platform. 1.1 Module

More information

NoSQL and Hadoop Technologies On Oracle Cloud

NoSQL and Hadoop Technologies On Oracle Cloud NoSQL and Hadoop Technologies On Oracle Cloud Vatika Sharma 1, Meenu Dave 2 1 M.Tech. Scholar, Department of CSE, Jagan Nath University, Jaipur, India 2 Assistant Professor, Department of CSE, Jagan Nath

More information

Data Services Advisory

Data Services Advisory Data Services Advisory Modern Datastores An Introduction Created by: Strategy and Transformation Services Modified Date: 8/27/2014 Classification: DRAFT SAFE HARBOR STATEMENT This presentation contains

More information

CSE 590: Special Topics Course ( Supercomputing ) Lecture 10 ( MapReduce& Hadoop)

CSE 590: Special Topics Course ( Supercomputing ) Lecture 10 ( MapReduce& Hadoop) CSE 590: Special Topics Course ( Supercomputing ) Lecture 10 ( MapReduce& Hadoop) Rezaul A. Chowdhury Department of Computer Science SUNY Stony Brook Spring 2016 MapReduce MapReduce is a programming model

More information

Introduction to NoSQL Databases. Tore Risch Information Technology Uppsala University 2013-03-05

Introduction to NoSQL Databases. Tore Risch Information Technology Uppsala University 2013-03-05 Introduction to NoSQL Databases Tore Risch Information Technology Uppsala University 2013-03-05 UDBL Tore Risch Uppsala University, Sweden Evolution of DBMS technology Distributed databases SQL 1960 1970

More information

Big Data With Hadoop

Big Data With Hadoop With Saurabh Singh singh.903@osu.edu The Ohio State University February 11, 2016 Overview 1 2 3 Requirements Ecosystem Resilient Distributed Datasets (RDDs) Example Code vs Mapreduce 4 5 Source: [Tutorials

More information

Hadoop s Entry into the Traditional Analytical DBMS Market. Daniel Abadi Yale University August 3 rd, 2010

Hadoop s Entry into the Traditional Analytical DBMS Market. Daniel Abadi Yale University August 3 rd, 2010 Hadoop s Entry into the Traditional Analytical DBMS Market Daniel Abadi Yale University August 3 rd, 2010 Data, Data, Everywhere Data explosion Web 2.0 more user data More devices that sense data More

More information

Azure Data Lake Analytics

Azure Data Lake Analytics Azure Data Lake Analytics Compose and orchestrate data services at scale Fully managed service to support orchestration of data movement and processing Connect to relational or non-relational data

More information

You should have a working knowledge of the Microsoft Windows platform. A basic knowledge of programming is helpful but not required.

You should have a working knowledge of the Microsoft Windows platform. A basic knowledge of programming is helpful but not required. What is this course about? This course is an overview of Big Data tools and technologies. It establishes a strong working knowledge of the concepts, techniques, and products associated with Big Data. Attendees

More information

ESS event: Big Data in Official Statistics. Antonino Virgillito, Istat

ESS event: Big Data in Official Statistics. Antonino Virgillito, Istat ESS event: Big Data in Official Statistics Antonino Virgillito, Istat v erbi v is 1 About me Head of Unit Web and BI Technologies, IT Directorate of Istat Project manager and technical coordinator of Web

More information

Lecture 32 Big Data. 1. Big Data problem 2. Why the excitement about big data 3. What is MapReduce 4. What is Hadoop 5. Get started with Hadoop

Lecture 32 Big Data. 1. Big Data problem 2. Why the excitement about big data 3. What is MapReduce 4. What is Hadoop 5. Get started with Hadoop Lecture 32 Big Data 1. Big Data problem 2. Why the excitement about big data 3. What is MapReduce 4. What is Hadoop 5. Get started with Hadoop 1 2 Big Data Problems Data explosion Data from users on social

More information

June 2015. JMS and Hadoop Agent. Automic Workload Automation

June 2015. JMS and Hadoop Agent. Automic Workload Automation June 2015 JMS and Hadoop Agent Automic Workload Automation + Hadoop Agent Demonstration Structure of Automic Hadoop Connection Hadoop use cases Demonstration + Feature Introduction + JMS Agent Demonstration

More information

NoSQL in der Cloud Why? Andreas Hartmann

NoSQL in der Cloud Why? Andreas Hartmann NoSQL in der Cloud Why? Andreas Hartmann 17.04.2013 17.04.2013 2 NoSQL in der Cloud Why? Quelle: http://res.sys-con.com/story/mar12/2188748/cloudbigdata_0_0.jpg Why Cloud??? 17.04.2013 3 NoSQL in der Cloud

More information

Spark in Action. Fast Big Data Analytics using Scala. Matei Zaharia. www.spark- project.org. University of California, Berkeley UC BERKELEY

Spark in Action. Fast Big Data Analytics using Scala. Matei Zaharia. www.spark- project.org. University of California, Berkeley UC BERKELEY Spark in Action Fast Big Data Analytics using Scala Matei Zaharia University of California, Berkeley www.spark- project.org UC BERKELEY My Background Grad student in the AMP Lab at UC Berkeley» 50- person

More information

International Journal of Advancements in Research & Technology, Volume 3, Issue 2, February-2014 10 ISSN 2278-7763

International Journal of Advancements in Research & Technology, Volume 3, Issue 2, February-2014 10 ISSN 2278-7763 International Journal of Advancements in Research & Technology, Volume 3, Issue 2, February-2014 10 A Discussion on Testing Hadoop Applications Sevuga Perumal Chidambaram ABSTRACT The purpose of analysing

More information

Big Data and Data Science: Behind the Buzz Words

Big Data and Data Science: Behind the Buzz Words Big Data and Data Science: Behind the Buzz Words Peggy Brinkmann, FCAS, MAAA Actuary Milliman, Inc. April 1, 2014 Contents Big data: from hype to value Deconstructing data science Managing big data Analyzing

More information

Hadoop Ecosystem B Y R A H I M A.

Hadoop Ecosystem B Y R A H I M A. Hadoop Ecosystem B Y R A H I M A. History of Hadoop Hadoop was created by Doug Cutting, the creator of Apache Lucene, the widely used text search library. Hadoop has its origins in Apache Nutch, an open

More information

Big Data Management and Security

Big Data Management and Security Big Data Management and Security Audit Concerns and Business Risks Tami Frankenfield Sr. Director, Analytics and Enterprise Data Mercury Insurance What is Big Data? Velocity + Volume + Variety = Value

More information

Google Bing Daytona Microsoft Research

Google Bing Daytona Microsoft Research Google Bing Daytona Microsoft Research Raise your hand Great, you can help answer questions ;-) Sit with these people during lunch... An increased number and variety of data sources that generate large

More information

Big Data Technology ดร.ช ชาต หฤไชยะศ กด. Choochart Haruechaiyasak, Ph.D.

Big Data Technology ดร.ช ชาต หฤไชยะศ กด. Choochart Haruechaiyasak, Ph.D. Big Data Technology ดร.ช ชาต หฤไชยะศ กด Choochart Haruechaiyasak, Ph.D. Speech and Audio Technology Laboratory (SPT) National Electronics and Computer Technology Center (NECTEC) National Science and Technology

More information

Big Data Training - Hackveda

Big Data Training - Hackveda Big Data Training - Hackveda Become a Hackveda Certified Big Data Professional - (Beginner) Skill level: Beginner Training fee: INR 9000 only (Topics covered: 108) Chief Trainer: Mr. Devanshu Shukla Training

More information

Monitis Project Proposals for AUA. September 2014, Yerevan, Armenia

Monitis Project Proposals for AUA. September 2014, Yerevan, Armenia Monitis Project Proposals for AUA September 2014, Yerevan, Armenia Distributed Log Collecting and Analysing Platform Project Specifications Category: Big Data and NoSQL Software Requirements: Apache Hadoop

More information

MongoDB and Couchbase

MongoDB and Couchbase Benchmarking MongoDB and Couchbase No-SQL Databases Alex Voss Chris Choi University of St Andrews TOP 2 Questions Should a social scientist buy MORE or UPGRADE computers? Which DATABASE(s)? Document Oriented

More information

Hadoop: A Framework for Data- Intensive Distributed Computing. CS561-Spring 2012 WPI, Mohamed Y. Eltabakh

Hadoop: A Framework for Data- Intensive Distributed Computing. CS561-Spring 2012 WPI, Mohamed Y. Eltabakh 1 Hadoop: A Framework for Data- Intensive Distributed Computing CS561-Spring 2012 WPI, Mohamed Y. Eltabakh 2 What is Hadoop? Hadoop is a software framework for distributed processing of large datasets

More information

Preparing Your Data For Cloud

Preparing Your Data For Cloud Preparing Your Data For Cloud Narinder Kumar Inphina Technologies 1 Agenda Relational DBMS's : Pros & Cons Non-Relational DBMS's : Pros & Cons Types of Non-Relational DBMS's Current Market State Applicability

More information

Affordable, Scalable, Reliable OLTP in a Cloud and Big Data World: IBM DB2 purescale

Affordable, Scalable, Reliable OLTP in a Cloud and Big Data World: IBM DB2 purescale WHITE PAPER Affordable, Scalable, Reliable OLTP in a Cloud and Big Data World: IBM DB2 purescale Sponsored by: IBM Carl W. Olofson December 2014 IN THIS WHITE PAPER This white paper discusses the concept

More information

BIG DATA Alignment of Supply & Demand Nuria de Lama Representative of Atos Research &

BIG DATA Alignment of Supply & Demand Nuria de Lama Representative of Atos Research & BIG DATA Alignment of Supply & Demand Nuria de Lama Representative of Atos Research & Innovation 04-08-2011 to the EC 8 th February, Luxembourg Your Atos business Research technologists. and Innovation

More information

Manifest for Big Data Pig, Hive & Jaql

Manifest for Big Data Pig, Hive & Jaql Manifest for Big Data Pig, Hive & Jaql Ajay Chotrani, Priyanka Punjabi, Prachi Ratnani, Rupali Hande Final Year Student, Dept. of Computer Engineering, V.E.S.I.T, Mumbai, India Faculty, Computer Engineering,

More information

Programming Hadoop 5-day, instructor-led BD-106. MapReduce Overview. Hadoop Overview

Programming Hadoop 5-day, instructor-led BD-106. MapReduce Overview. Hadoop Overview Programming Hadoop 5-day, instructor-led BD-106 MapReduce Overview The Client Server Processing Pattern Distributed Computing Challenges MapReduce Defined Google's MapReduce The Map Phase of MapReduce

More information

Open Source Technologies on Microsoft Azure

Open Source Technologies on Microsoft Azure Open Source Technologies on Microsoft Azure A Survey @DChappellAssoc Copyright 2014 Chappell & Associates The Main Idea i Open source technologies are a fundamental part of Microsoft Azure The Big Questions

More information

GridGain In- Memory Data Fabric: UlCmate Speed and Scale for TransacCons and AnalyCcs

GridGain In- Memory Data Fabric: UlCmate Speed and Scale for TransacCons and AnalyCcs GridGain In- Memory Data Fabric: UlCmate Speed and Scale for TransacCons and AnalyCcs DMITRIY SETRAKYAN Founder & EVP Engineering @dsetrakyan www.gridgain.com #gridgain Agenda EvoluCon of In- Memory CompuCng

More information

Big data and urban mobility

Big data and urban mobility Big data and urban mobility Antònia Tugores,PereColet Instituto de Física Interdisciplinar y Sistemas Complejos, IFISC(UIB-CSIC) Abstract. Data sources have been evolving the last decades and nowadays

More information

Вовченко Алексей, к.т.н., с.н.с. ВМК МГУ ИПИ РАН

Вовченко Алексей, к.т.н., с.н.с. ВМК МГУ ИПИ РАН Вовченко Алексей, к.т.н., с.н.с. ВМК МГУ ИПИ РАН Zettabytes Petabytes ABC Sharding A B C Id Fn Ln Addr 1 Fred Jones Liberty, NY 2 John Smith?????? 122+ NoSQL Database

More information

Hadoop implementation of MapReduce computational model. Ján Vaňo

Hadoop implementation of MapReduce computational model. Ján Vaňo Hadoop implementation of MapReduce computational model Ján Vaňo What is MapReduce? A computational model published in a paper by Google in 2004 Based on distributed computation Complements Google s distributed

More information

Moving From Hadoop to Spark

Moving From Hadoop to Spark + Moving From Hadoop to Spark Sujee Maniyam Founder / Principal @ www.elephantscale.com sujee@elephantscale.com Bay Area ACM meetup (2015-02-23) + HI, Featured in Hadoop Weekly #109 + About Me : Sujee

More information

Apache Ignite TM (Incubating) - In- Memory Data Fabric Fast Data Meets Open Source

Apache Ignite TM (Incubating) - In- Memory Data Fabric Fast Data Meets Open Source Apache Ignite TM (Incubating) - In- Memory Data Fabric Fast Data Meets Open Source DMITRIY SETRAKYAN Founder, PPMC http://www.ignite.incubator.apache.org @apacheignite @dsetrakyan Agenda About In- Memory

More information