No sql now2011_review_of_adhoc_architectures
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This document discusses architectures for enabling business intelligence and analytics on NoSQL data. It begins by outlining common questions around enabling ad-hoc reporting, improving dashboard performance, integrating data, and balancing simple and complex queries. It then reviews several architectures: using only NoSQL for reports, treating NoSQL as a data source, writing programs to access NoSQL in BI tools, and enabling SQL access to NoSQL data. Examples are provided of companies using different architectures, such as only NoSQL, NoSQL with MySQL, or NoSQL via a SQL database.
No sql now2011_review_of_adhoc_architectures
- 1. BI/Analytics for NoSQL: Review of Architectures
- 2. What we'll answer in 50 minutes • Who is this guy? • How do I enable AdHoc, self service reporting on NoSQL? • How do I improve the performance of dashboards on top of NoSQL? • How do I integrate NoSQL data with my other data not inside NoSQL? • How do I enable, easy to build simple reports but also preserve the ability for rich NoSQL queries?
- 3. Nicholas Goodman • Open Source BI thought leader – 50+ Open Source BI customer projects – Blogger, whitepapers, etc • Entrepreneur – DynamoBI Corporation – Bayon Technologies, Inc. • Data Geek, hacker, tinkerer, committer GOAL: Share perspectives, research, opinions. DISCLAIMER: Your Mileage ...
- 4. How do we answer those Q's?
- 5. Promise of “Big Data” • NoSQL/Hadoop/MapReduce Systems – Keep more of it – Cost effective analysis – “Massive scale” data, now accessible to everyone (elastic) – Not just SQL queries, more complex analysis ACCOMPLISHED: WEB SCALE, MASSIVE NEVER BEFORE SEEN SCALE OF DATA STORAGE AND PROCESSING
- 6. Reality Check! • Petabytes? Y • Fast Queries? N • Cheap Storage? Y • Ad Hoc access? N • Raw Processing? Y • Accessibility to commodity BI tools? N • Rich Query Languages? Y • Flexible data structures? Y• Easy report authoring? N • Reliable, Fault Tolerant? Y• Levels of Aggregation? N • Integrated Data? N Big Data has solved the INFRASTRUCTURE of raw/core data storage but has provided less value to what BUSINESS users want for analytics.
- 7. Data Gaps too! • Code, Developers • Analysts w/ Excel, Dashboards • MR, Rich Graph/Access • Simple 2D (tables, charts) • Hierarchical, Unstructured • Filtering and easy analytics
- 8. Levels of Aggregation SAME DATA AT VARIOUS LEVELS OF AGGREGATION HUGELY IMPORTANT IN REAL LIFE IMPLEMENTATIONS! 10K 1 ROW 1 MILLION TO 100 MILLION 1 BILLION ROWS 100 BILLION
- 9. Architectures • NoSQL reports • NoSQL thru and thru • NoSQL + MySQL • NoSQL as ETL Source • NoSQL programs in BI Tools • NoSQL via BI Database (SQL)
- 10. NoSQL reports • Pay Developer to build applications for reports Apps • 100% Richness of NoSQL • $$, developer driven process • Up to date, current • No commodity BI tools • Excellent performance on • Managing rollups/summaries large datasets • Schema-less = Harder! • Custom built, beautiful • Hard to integrate other reports/dashboards reporting information • Single system to manage
- 11. NoSQL thru and thru • Pay Developer to build FLEXIBLE applications for reports Indices Advanced Aggs Apps • All of NoSQL report • $$, developer driven process advantages • $$, app required for aggs • Managed aggregations, • No commodity BI tools rollups • Hard to integrate other • “Guided Adhoc” available reporting information inside application • Limited AdHoc (only • Higher performance for developer built dashboards/summaries combinations)
- 12. NoSQL + MySQL • Pay Developer to build FLEXIBLE applications for reports ETL App MySQL • Less IT $$ since developers • Data freshness (24 hrs old) aren't “building reports” • Once into MySQL no rich • Rich, NoSQL analysis left in NoSQL application use (M/R) place (ETL + NoSQL) • BI Tool can connect ONLY to • Easy, Ad Hoc reporting via data in MySQL, not NoSQL commodity BI tools • Aggregations still self • Easier to understand data for managed in MySQL self service reports
- 13. NoSQL as ETL Data Source • NoSQL treated like any other data source Informatica Teradata • Allows use of consolidated, • ETL Development Expense BI tool for AdHoc • Data Latency • Enables integrated • Loss of NoSQL language (combined) datasets for richness reporting • Traditional DW tools are $$ • Aggregations Often “managed” • Scaling issues with DW Database • Best of Breed tools
- 14. NoSQL programs in BI Tools • Write a program in BI tool that flattens data, output into report • Rich use of NoSQL native • Developer required to write language program ($$) • Direct, up to date access • Slow-er (aggs, summaries) • Access to 100% of dataset • Lacks integration with other • Leverage “guided” report datasets parameter pages • Still (usually) no AdHoc • Less expensive than apps access
- 15. NoSQL via BI Database (SQL) • Enable NoSQL data access via SQL (gasp!) Live Query Cached, 24hr data • Easy reports, easy (SQL) • Another system in between • Integration with other data • Still needs to be refreshed, • ETL is simple INSERT/MERGEs nightly • Live, up to date access • Not all capabilities for NoSQL richness available via SQL • High performance, cached data • AdHoc access to Live + Cached • Aggregations/Summaries
- 16. Mozilla: NoSQL thru and thru(DB) • Socorro Project: Crash reports, optionally sent to Mozilla • https://crash-stats.mozilla.com
- 17. X: NoSQL via SQL • Using “Splunk” (ie, a commercial NoSQL-eee data aggregator/etc) • Desire to use Tableau for advanced analytics/visualization
- 18. Meteor Solutions: NoSQL thru and thru • Using Cloudant BigCouch solution (SaaS) • High performance set of multi purpose indices on pre defined aggregations • Up to date aggregation/reports • Better fit for Social Media graph structures over relational DB • Custom built BI applications (dashboards/reports) providing a flexible guided view through data Advanced Apps
- 19. A,B,C: NoSQL + MySQL • Many Many companies (3 we've worked with) • All “web related” companies (semi structured, some, mostly volume) • Heavy lifting and storage, and “ETL/Data prepartion” inside Hadoop • Push summarized, aggregated data into MySQL for analysis by easy, dashboarding/BI Tools ETL App MySQL