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Webinar Your Enterprise Database Strategy 2014

Webinar Your Enterprise Database Strategy 2014. Noel Yuhanna, Principal Analyst. March 4, 2014. Call in at 12:55 p.m. Eastern time. Teleconference. Business growth and speed are changing the database requirements. Agenda. Current drivers and trends for databases

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Webinar Your Enterprise Database Strategy 2014

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  1. WebinarYour Enterprise Database Strategy 2014 Noel Yuhanna, Principal Analyst March 4, 2014. Call in at 12:55 p.m. Eastern time Teleconference

  2. Business growth and speed are changing the database requirements . . .

  3. Agenda • Current drivers and trends for databases • Changes in data and app requirements • Your enterprise database strategy in 2014 • Recommendations

  4. Agenda • Current drivers and trends for databases • Changes in data and app requirements • Your enterprise database strategy in 2014 • Recommendations

  5. Performance, integration, and resources are top database challenges Base: 104 database management professionals (multiple responses accepted); Source: February 2013 Global Database Management Online Survey

  6. Drivers and trends affecting databases • Increased transaction volume • New apps — social, mobile apps • Increased data volumes • Cost control and stalled budget • Nonstop 24x7 availability • Faster real-time data access • Strong data security controls • Integrated app/data • All types of data storage • Unpredictable workloads DBMS strategy

  7. Agenda • Current drivers and trends for databases • Changes in data and app requirements • Your enterprise database strategy in 2014 • Recommendations

  8. New applications are changing database requirements . . . Real-time data Faster access Unstructured data Self-service Automated Many are building a dozen apps every week!! Social networking apps Mobile applications High-performance apps Real-time apps Real-time data mashups Departmental and collaboration Predictive analytics

  9. Database appliances are mainstream High performance Integrated Scalable Single vendor Automated Improved SLAs Oracle Others HP IBM Teradata

  10. Falling memory prices and new in-memory technologies offer new possibilities . . . In-memory database Falling memory prices 1. Memory prices were at $100,000 per gigabyte in 1990; they are down to $5 per gigabyte in 2012. 2. Data stored in cache/memory can be accessed 20x to 50x faster than the disk. 3. In-memory database and distributed cluster deliver powerful horizontal scale.

  11. Databases need to support more than structured relational data — be prepared . . . You need more than RDBMS! Structured Hadoop can help . . . Unstructured NoSQL DBMS can help . . . Semistructured

  12. Hadoop can help process large amounts of data which is difficult to do in databases . . . Large amounts of data • Open source software that enables distributed parallel processing of large amounts of data across low-cost commodity servers • It leverages an extensible framework for building advanced analytics and new data management capabilities. • It’s already being commercialized and adopted rapidly in enterprises. Hadoop Flexible Distributed processing Economical Scalable Open source Insights

  13. Social networking, including apps, is changing the way data is accessed and managed Jive Microsoft SharePoint

  14. New business requirements are making older data management methods inadequate • New applications: • Social networking • Mobile applications • High-performance • Business intelligence • Real-time data mashup • Departmental and collaboration Business challenges: Need for real-time data has grown Delivering solutions more quickly Delivering more scalable solution Ensuring cost effectiveness Technology challenges: Increasing data volume Ensuring 24x7 global availability Increasing number of users

  15. Agenda • Current drivers and trends for databases • Changes in data and app requirements • Your enterprise database strategy in 2014 • Recommendations

  16. Oracle and SQL Server dominate in transactional applications Base: 104 database management professionals (multiple responses accepted); Source: February 2013 Global Database Management Online Survey

  17. Database categorization based on function Source: June 7, 2013, “The Steadily Growing Database Market Is Increasing Enterprises’ Choices” Forrester report

  18. TechRadar: Database Management 2014 Source: February 13, 2014, “TechRadar™: Enterprise DBMS, Q1 2014” Forrester report

  19. Data warehouse strategy

  20. What’s new in data warehouses? Appliances, appliances, appliances Larger EDWs — 100s of TBs EHL — Extract Hadoop Load Focus toward real-time data More decentralized data warehouses Cloud databases are gaining grounds.

  21. Next-generation EDW platform Source: December 9, 2013, “The Forrester Wave™: Enterprise Data Warehouse, Q4 2013” Forrester report

  22. Oracle, Microsoft, and IBM dominate the data warehouse category Base: 104 database management professionals (multiple responses accepted); Source: February 2013 Global Database Management Online Survey

  23. The Forrester Wave™: Enterprise Data Warehouse, Q4 ’13 Source: December 9, 2013, “The Forrester Wave™: Enterprise Data Warehouse, Q4 2013” Forrester report

  24. The Forrester Wave™: Enterprise Data Warehouse, Q4 ’13 (Cont.) Source: December 9, 2013, “The Forrester Wave™: Enterprise Data Warehouse, Q4 2013” Forrester report

  25. NoSQL strategy

  26. NoSQL gains momentum Why use it? Cost, performance, scale, and availability Why not use it? Manageability, staffing, and support Three key categories for NoSQL: Key value, document, and graph

  27. NoSQL use cases . . . Customer personalization app — age of the customer Social media app — Facebook, Twitter, LinkedIn, Craigslist . . . Recommendation engine — connected data Mobile application Real-time analytics Mashup applications Embedded databases for ISV and VARs Elastic caching applications Scale-out analytical workloads Fraud detection apps Real-time monitoring

  28. Cloud databases

  29. Public cloud databases are viable to support mission-critical applications . . . Database Adoption of cloud database is around 14%. It will double over the next two years. Key benefits: On-demand scale Automated Easy to provision Cost effective Better availability

  30. Public cloud databases are viable to support mission-critical applications . . . (cont.) Database Challenges: Security Latency SLAs Automated scale

  31. Cloud database use cases . . . • Mobile applications • eCommerce app running completely in the public cloud using cloud database • Analytics and predictive analytics in the cloud • Social media apps • Data services apps • SaaS applications • Departmental apps • LOB — marketing, sales, finance, HR, and engineering apps • Small group apps • Departmental collaboration

  32. Cloud database use cases . . . (cont.) • Application development and testing • Provision new databases quickly in the cloud. • Support app development. • Support app testing. • SMB applications • All types of SMB apps • Database backup and archive • Keeping another copy of their data in the cloud as backup • Database archive for long-term retention • And more . . .

  33. The Forrester Wave™: Enterprise Cloud Databases, Q4 ’12 Source: November 8, 2012, “The Forrester Wave: Enterprise Cloud Databases, Q4 2012” Forrester report

  34. The Forrester Wave™: Enterprise Cloud Databases, Q4 ’12 (cont.) Source: November 8, 2012, “The Forrester Wave: Enterprise Cloud Databases, Q4 2012” Forrester report

  35. Hadoop strategy

  36. What’s new in Hadoop . . . Forrester’s latest Hadoop wave! Many petabyte sized Hadoop implementations . . . Adoption of Hadoop is 20% . . . Another 33% by 2017! Hadoop ecosystem is growing . . . Gaps still exist. More use cases . . . Mostly dealing with structured data . . . unstructured data is ramping up.

  37. Big data platform Distributed in-memory Analytics/PA 10s TB into 100sTB streams Data virtualization Data integration Data hub/lake EDW 100’s TB into petabytes IOT (Hadoop) Big data

  38. The Forrester Wave™: Big Data Hadoop Solutions, Q1 ’14 Source: February 27, 2014, “The Forrester Wave: Big Data Hadoop Solutions, Q1 2014” Forrester report

  39. The Forrester Wave™: Big Data Hadoop Solutions, Q1 ’14 (cont.) Source: February 27, 2014, “The Forrester Wave: Big Data Hadoop Solutions, Q1 2014” Forrester report

  40. In-memory databases

  41. In-memory market landscape Gigaspaces, Terracotta, Gemstone, Oracle Coherence, others . . . Application-tier memory SAP HANA, MSFT, Oracle, IBM, Aerospike, VoltDB, MemSQL, Starcounter, Altibase Database-tier memory

  42. Performance, integration, and resources are top database challenges Source: June 7, 2013, “The Steadily Growing Database Market Is Increasing Enterprises’ Choices” Forrester report

  43. Trends around in-memory Increasing adoption of in-memory — currently at 27% adoption — additional 32% by 2017 Increased inquiries in in-memory by 200% compared to prior 12 months Most organizations struggling in performance -> 80% Increasing data volume growth putting pressure to process data more quickly Real-time analytics is gaining grounds. Age of customer — personalization . . .

  44. Use cases Retail/telco Real-time personalization, recommendation engine, predictive Mobile applications Operational analytics, real-time apps . . . Gaming Real-time analysis of gaming — top scorer, ratings, virtual store . . . Financial services Fraud detection, risk-management, online trading Media/advertising Clickstream, impressions, real-time analysis Manufacturing Improve efficiencies of machines, proactive checks for turbines, aircraft Others

  45. By 2017, more than half of enterprises will be running in-memory applications and analytics . . . Real-time analytics Mobile applications Web apps Packaged apps Custom apps High-end transactional app Big data analytics Scientific apps

  46. In-memory delivers faster actionable results and new insights . . . and even transactions . . . Data in-memory offers faster real-time data access, processes large amounts of data quickly, and offers new insights and opportunities . . . Trans. Real-time Faster Scalable Advanced analytics Distributed in-memoryfabric (Horizontalscale) servers servers Big data Clickstream CRM Logs Social media

  47. Agenda • Current drivers and trends for databases • Changes in data and app requirements • Key DBMS vendors • Your enterprise database strategy in 2014 • Recommendations

  48. Recommendations DBMS can handle multiple terabytes of data. Eighty percent of your apps can be supported by any of the top RDBMS products; 20% need a new approach — such as NoSQL, XML DB, open source, etc. (scale-out sharding, schema-less architecture, document database, etc.) Look at upgrading to newer releases to reduce administration cost and improve availability. NoSQL has become mature. It’s time to have its part of your strategy. Database appliances should be part of your DBMS strategy. In-memory is critical — if you don’t have it, you’ll be left behind. To lower cost, look at cloud database, database consolidation, clustering, standardization of DBMS, and automation.

  49. Noel Yuhanna +1 650.581.3807 nyuhanna@forrester.com www.forrester.com

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