Budapest Spring MUG 2016 - MongoDB User Group
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The document outlines the key features and enhancements of MongoDB 3.2, including the introduction of the WiredTiger storage engine, which offers improved performance and encryption capabilities. It highlights advanced data governance tools, in-database analytics, and management enhancements that simplify operations for both developers and database administrators. The updates aim to optimize MongoDB for mission-critical applications while providing new insights and capabilities for business analysts and data scientists.
Budapest Spring MUG 2016 - MongoDB User Group
- 1. Overview for The Budapest MUG What’s New in MongoDB 3.2 Marc Schwering Sr. Solu1on Architect – EMEA e: marc@mongodb.com t: @m4rcsch
- 2. Storage Engines Broaden Use Cases
- 3. Storage Engine Architecture in 3.2 Content Repo IoT Sensor Backend Ad Service Customer Analytics Archive MongoDB Query Language (MQL) + Native Drivers MongoDB Document Data Model WT MMAP Supported in MongoDB 3.2 Management Security In-memory (beta) Encrypted 3rd party
- 4. WiredTiger is the New Default WiredTiger – widely deployed with 3.0 – is now the default storage engine for MongoDB. • Best general purpose storage engine • 7-10x better write throughput • Up to 80% compression
- 5. Encrypted Storage Engine Encrypted storage engine for end-to-end encryption of sensitive data in regulated industries • Reduces the management and performance overhead of external encryption mechanisms • AES-256 Encryption, FIPS 140-2 option available • Key management: Local key management via keyfile or integration with 3rd party key management appliance via KMIP • Offered as an option for WiredTiger storage engine
- 6. In-Memory Storage Engine (Beta) Handle ultra-high throughput with low latency and high availability • Delivers the extreme throughput and predictable latency required by the most demanding apps in Adtech, finance, and more. • Achieve data durability with replica set members running disk-backed storage engine • Available for beta testing and is expected for GA in early 2016
- 7. One Deployment Powering MultipleApps
- 8. Built for Mission Critical Deployments
- 9. Data Governance with Document Validation Implement data governance without sacrificing agility that comes from dynamic schema • Enforce data quality across multiple teams and applications • Use familiar MongoDB expressions to control document structure • Validation is optional and can be as simple as a single field, all the way to every field, including existence, data types, and regular expressions
- 10. Document Validation Example The example on the left adds a rule to the contacts collection that validates: • The year of birth is no later than 1994 • The document contains a phone number and / or an email address • When present, the phone number and email addresses are strings
- 11. Enhancements for your mission-critical apps More improvements in 3.2 that optimize the database for your mission-critical applications • Meet stringent SLAs with fast-failover algorithm – Under 2 seconds to detect and recover from replica set primary failure • Simplified management of sharded clusters allow you to easily scale to many data centers – Config servers are now deployed as replica sets; up to 50 members
- 12. Tools for UsersAcross Your Organization
- 13. For Business Analysts & Data Scientists MongoDB 3.2 allows business analysts and data scientists to support the business with new insights from untapped data sources • MongoDB Connector for BI • Dynamic Lookup • New Aggregation Operators & Improved Text Search
- 14. MongoDB Connector for BI Visualize and explore multi-dimensional documents using SQL-based BI tools. The connector does the following: • Provides the BI tool with the schema of the MongoDB collection to be visualized • Translates SQL statements issued by the BI tool into equivalent MongoDB queries that are sent to MongoDB for processing • Converts the results into the tabular format expected by the BI tool, which can then visualize the data based on user requirements ⇒ h=ps://www.mongodb.com/download-center?jmp=hero#bi-connector
- 15. Dynamic Lookup Combine data from multiple collections with left outer joins for richer analytics & more flexibility in data modeling • Blend data from multiple sources for analysis • Higher performance analytics with less application- side code and less effort from your developers • Executed via the new $lookup operator, a stage in the MongoDB Aggregation Framework pipeline
- 16. Conceptual Model ofAggregation Framework Start with the original collection; each record (document) contains a number of shapes (keys), each with a particular color (value) • $match filters out documents that don’t contain a red diamond • $project adds a new “square” attribute with a value computed from the value (color) of the snowflake and triangle attributes
- 17. Conceptual Model ofAggregation Framework • $lookup performs a left outer join with another collection, with the star being the comparison key • Finally, the $group stage groups the data by the color of the square and produces statistics for each group
- 18. Improved In-DatabaseAnalytics & Search New Aggregation operators extend options for performing analytics and ensure that answers are delivered quickly and simply with lower developer complexity • Array operators: $slice, $arrayElemAt, $concatArrays, $filter, $min, $max, $avg, $sum, and more • New mathematical operators: $stdDevSamp, $stdDevPop, $sqrt, $abs, $trunc, $ceil, $floor, $log, $pow, $exp, and more • Case sensitive text search and support for additional languages such as Arabic, Farsi, Chinese, and more
- 19. For Database Administrators MongoDB 3.2 helps users in your organization understand the data in your database • MongoDB Compass – For DBAs responsible for maintaining the database in production – No knowledge of the MongoDB query language required
- 20. MongoDB Compass For fast schema discovery and visual construction of ad-hoc queries • Visualize schema – Frequency of fields – Frequency of types – Determine validator rules • View Documents • Graphically build queries • Authenticated access ⇒ h=ps://www.mongodb.com/download-center?jmp=hero#compass
- 21. For Operations Teams MongoDB 3.2 simplifies and enhances MongoDB’s management platforms. Ops teams can be 10-20x more productive using Ops and Cloud Manager to run MongoDB. • Start from a global view of infrastructure: Integrations with Application Performance Monitoring platforms • Drill down: Visual query performance diagnostics, index recommendations • Then, deploy: Automated index builds • Refine: Partial indexes improve resource utilization
- 22. Integrations with APM Platforms Easily incorporate MongoDB performance metrics into your existing APM dashboards for global oversight of your entire IT stack • MongoDB drivers enhanced with new API that exposed query performance metrics to APM tools • In addition, Ops and Cloud Manager can complement this functionality with rich database monitoring.
- 23. Query Perf. Visualizations & Optimization Fast and simple query optimization with the new Visual Query Profiler • Query and write latency are consolidated and displayed visually; your ops teams can easily identify slower queries and latency spikes • Visual query profiler analyzes the data it displays and provides recommendations for new indexes that can be created to improve query performance • Ops Manager and Cloud Manager can automate the rollout of new indexes, reducing risk and your team’s operational overhead
- 24. Refine with Partial Indexes Balance delivering good query performance while consuming fewer system resources • Specify a filtering expression during index creation to instruct MongoDB to only include documents that meet your desired conditions • The example to the left creates a compound index that only indexes the documents with the rating field greater than 5
- 25. Ops Manager Enhancements 3.2 includes Ops Manager enhancements to improve the productivity of your ops teams and further simplify installation and management • MongoDB backup on standard network-mountable filesystems; integrates with your existing storage infrastructure • Automated database restores; Build clusters from backup in a few clicks • Faster time to first database snapshot • Support for maintenance windows • Centralized UI for installation and config of all application and backup components
- 26. Thank you! Marc Schwering Sr. Solutions Architect – EMEA marc@mongodb.com @m4rcsch