MongoDB 3.2 Feature Preview
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MongoDB 3.2 introduces significant enhancements including hash-based sharding, new storage engines, and improved management of sharded clusters. Key features like document validation and encryption at rest focus on governance and data security, while tools such as MongoDB Compass and the BI connector enhance usability for data analysts and DBAs. The release aims to optimize performance for mission-critical applications and offers advanced query optimization tools for better analytics and search capabilities.
MongoDB 3.2 Feature Preview
- 2. MongoDB 3.2 – a BIG Release Hash-Based Sharding Roles Kerberos On-Prem Monitoring 2.2 2.4 2.6 3.0 3.2 Agg. Framework Location-Aware Sharding $out Index Intersection Text Search Field-Level Redaction LDAP & x509 Auditing Document Validation Fast Failover Simpler Scalability Aggregation ++ Encryption At Rest In-Memory Storage Engine BI Connector $lookup MongoDB Compass APM Integration Profiler Visualization Auto Index Builds Backups to File System Doc-Level Concurrency Compression Storage Engine API ≤50 replicas Auditing ++ Ops Manager
- 3. Themes
- 4. Themes Broader use case portfolio. Pluggable storage engine strategy enables us to rapidly cover more use cases with a single database. Mission-critical apps. MongoDB delivers major advances in the critical areas of governance, high availability, and disaster recovery. New tools for new users. Now MongoDB is an integral part of the tooling and workflows of Data Analysts, DBAs, and Operations teams.
- 6. 6 Varying Access & Storage Requirements Modern apps Sensitive data Cost effective storage High concurrency High throughput Low latency Real-time analytics
- 7. 7 Flexible Storage Architecture in 3.2
- 8. 8 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
- 9. 9 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 • Based on WiredTiger storage engine • Requires MongoDB Enterprise Advanced
- 10. 10 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
- 12. 12 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
- 13. 13 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
- 14. 14 Document Validation What you get • 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. More power to the DBAs • The DBA can specify which documents in a collection should be validated • Failed validations can be configured – Hard error – Just a warning
- 16. 16 Simplified Sharded Cluster Management What you get • Simplified sharded deployments – Config servers are deployed as replica sets • Improved metadata consistency • Easily scale to many data centers
- 17. Config server replica sets can span more than 3 data centers with up to 50 replica set members supported
- 18. Enhancements for your mission-critical apps More improvements in 3.2 that optimize the database for your mission-critical applications • Meet stringent SLAs with Raft-base fast-failover algorithm – Under 2 seconds to detect and recover from replica set primary failure – Enhanced durability through write conerns • 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/locations
- 19. 19 Fast Failover The Improvements • Enhanced algorithm detects failure and isolation of primary in replica set – Reduces interval between primary failure and the replacement – Resolves false-positives caused by network glitches – Allows efficient intra-cluster communications, even as the replica set grows What you get • No more than 2 seconds to detect and recover replica set primary failure – Exact time is dependent on system configuration – Tune the timing with the electionTimeoutMillis parameter • Clusters more resilient to overloaded or unreliable networks
- 20. New Tools for New Users
- 21. DBAs 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
- 22. Operations Integration with standard operational workflow reduces overhead • Start from global view of infrastructure: APM tools integration, e.g. New Relic, AppDynamics. • Then, drill down: Profiler visualization in Ops Manager • Then, deploy: Automated index builds • Next, refine: Partial Indexes improve resource utilization
- 23. 23 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
- 24. 24 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
- 25. 25 Dynamic Lookup Combine data from multiple collections with left outer joins for richer analytics & more flexibility in data modeling • Blend data from multiple collections 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
- 26. 26 Improved In-Database Analytics & 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 • Random sample of documents: $sample • Case sensitive text search and support for additional languages such as Arabic, Farsi, Chinese, and more
- 27. 27 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
- 28. 28 Next Steps • Download the Whitepaper – https://www.mongodb.com/collateral/mongodb-3-2-whats-new • Read the Release Notes – https://docs.mongodb.org/manual/release-notes/3.2/ • Not yet ready for production but download and try! – https://www.mongodb.org/downloads#development • Detailed blogs – https://www.mongodb.com/blog/ • Feedback – MongoDB 3.2 Bug Hunt • https://www.mongodb.com/blog/post/announcing-the-mongodb-3-2-bug-hunt – https://jira.mongodb.org/ DISCLAIMER: MongoDB's product plans are for informational purposes only. MongoDB's plans may change and you should not rely on them for delivery of a specific feature at a specific time.