Better Together: The New Data Management Orchestra
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This document discusses the evolution of data management technologies from early systems like Hadoop and NoSQL databases to modern approaches that combine these technologies. It notes that Hadoop focused on processing large amounts of multi-structured data using Apache components on commodity hardware, while NoSQL databases addressed use cases that were difficult for relational databases. The document outlines how companies like Teradata, Cloudera, and MongoDB now offer unified platforms that bring together relational, NoSQL, and analytics capabilities. A panel discussion is advertised on better integrating these technologies to enable data-driven enterprises.
Better Together: The New Data Management Orchestra
- 1. 1 Better Together: The New Data Management Orchestra
- 2. 2 Moderator Colin White • President and Founder of BI Research and DataBase Associates • Covers data management, information integration and BI
- 3. 3 Hadoop Beginnings: Apache Source: Microsoft “A framework for running applications on a large hardware cluster built of commodity hardware.” wiki.apache.org/hadoop/ Focus was on programmatic and batch-oriented applications that processed large amounts of multi-structured data (the original “big data”) Systems were deployed by assembling Apache components or using Hadoop distributions from companies such as Cloudera, Hortonworks and MapR
- 4. 4 NoSQL Beginnings (Examples) Focus was on use cases and types of data that were difficult to implement using a relational database approach – “non-relational” is a more appropriate term to use than “NoSQL.” Non-relational systems are not new, but earlier products were usually proprietary.
- 5. The DW Today: Teradata Example Past Today Single Platform to Solve All Problems Unified Architecture Data Query Single Database Query Multi-Databases and Sources SQL Multi Language (SQL/R/Java/Perl/Ruby/Python) Structured Data Structured and XML/JSON/Weblogs Business Users Business Users, Data Scientists, & Developers Disk Data Storage Hybrid Storage with Solid State Drives Standard Caching Intelligent Memory Row Data Storage Hybrid Row/Column Data Storage On-prem Dedicated Systems Public, Private and Hosted CloudAgile Phased; Incremental Delivery; BI SS
- 6. 6 A Lot Has Changed: Cloudera Example Relational and NoSQL Database Enterprise Data Hub Data Applications Data Sources Custom Applications Cloudera positioning: “The Enterprise Data Hub Complements the Ecosystem”
- 7. 7 Our Panelists Kelly Stirman, Director of Products, MongoDB Chris Twogood, VP of Product and Services Marketing, Teradata Charles Zedlewski, VP of Products, Cloudera
- 9. 9 Enabling the Data-Driven Enterprise
- 10. 10 Skills and Expertise
- 11. 11 Bringing It All Together
- 12. 12 Q&A
- 13. 13 Join us • Hadoop World – Oct. 15-17, NYC • Teradata PARTNERS – Oct. 19-23, Nashville • MongoDB Days – Coming to a city near you
- 14. 14 THANK YOU
Editor's Notes
- #8: Colin White Colin White is the founder of BI Research and president of DataBase Associates Inc. As an analyst, educator and writer he is well known for his in-depth knowledge of data management, information integration, and business intelligence technologies and how they can be used for building the smart and agile business. With many years of IT experience, he has consulted for dozens of companies throughout the world and is a frequent speaker at leading IT events. Colin has written numerous articles and papers on deploying new and evolving information technologies for business benefit and is a regular contributor to several leading print- and web-based industry journals. For ten years he was the conference chair of the Shared Insights Portals, Content Management, and Collaboration conference. He was also the conference director of the DB/EXPO trade show and conference.