MongoDB 3.3.5 is released

MongoDB
May 1, 2016
#Releases

MongoDB 3.3.5 has been released. As a reminder, 3.3.5 is a development release and is not intended for production use. The 3.3 series will evolve into 3.4, which will be for production.

New/fixed in this release:

SERVER-6823 Enable Access control without downtime
SERVER-10689 Add a $switch expression
SERVER-17258 Add $reduce expression operator for rollup of arrays
SERVER-20224 Commands which write should take a write concern
SERVER-23271 Add metrics to track index key additions and deletions for all CRUD ops/commands
SERVER-23358 Upgrade SpiderMonkey to 45.0.2 ESR
SERVER-23391 Improve behavior when running under WiredTiger on machines with little memory

All Issues | Downloads

As always, please let us know of any issues.

– The MongoDB Team

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MongoDB 3.2.6-rc0 is released

MongoDB 3.2.6-rc0 is out and is ready for testing. This is a release candidate containing only fixes since 3.2.5. The next stable release 3.2.6 will be a recommended upgrade for all 3.2 users. MongoDB 3.2.6 includes the first production release of the In-Memory storage engine. For more details see https://docs.mongodb.org/manual/core/inmemory/ Fixed in this release: SERVER-22970 Background index contains mismatched index keys and documents SERVER-22043 count helper doesn’t apply read preference SERVER-23394 AuthorizationManager may deadlock while building role graph if profiling is enabled SERVER-23766 Remove beta startup warning for inMemory storage engine All Issues | Downloads | Release Notes As always, please let us know of any issues. – The MongoDB Team

May 1, 2016

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Non-relational alternatives to relational databases — usually referred to as NoSQL databases — have been rapidly gaining popularity over the past decade. In 2013, MongoDB published one of our most popular white papers, “Top 5 Considerations When Evaluating NoSQL Databases.” We have since updated that paper as the technology has evolved. MongoDB is now offering a major update, which adds two new issues organizations should include in their thinking: how a database handles data generated at the edge by mobile devices and how a database fits into a broader data platform that includes search and analytics. If you’re testing the waters of NoSQL databases, then you’re probably familiar with how they’re different from traditional relational databases. The list of things you already know about NoSQL probably looks something like this: They use a different data model and query language. They have dynamic schemas. They scale horizontally. Beyond those common features, there are significant differences among NoSQL databases. The seven areas of significant differences among your options are: Data model (document, graph, key-value, etc.) Query model Consistency and transactional model APIs Mobile data Data platform Commercial support, community strength, and lock-in From MongoDB’s point of view, the most important consideration is the data model. We popularized the document model , which supports a superset of all data models, making it useful for a wide variety of applications. Key features include the ability to index and query in any field, and the natural mapping of document data structures to objects in modern programming languages. Recent shifts in how modern applications are developed and deployed — and in the experiences they offer customers — highlight the two new considerations. Mobile use cases: Mobile applications introduce the added challenge of not always being connected to the network. Developers need a solution for keeping all their customers’ apps in sync with the back-end database, no matter where they are in the world and what kind of network connection they have. The solution also needs to scale easily and quickly as more users download an app, and support the cutting edge of mobile development technologies as they evolve. Data platform: MongoDB’s application data platform provides developers a unified interface to serve transactional and operational applications alongside search, real-time, and data lake application needs. It eliminates the overhead and friction of developers having to stitch together multiple discrete technologies into a complex architecture, each creating its own duplicated data silo — connected by fragile ETL pipelines — and accessed, secured, governed, and operationalized by different APIs and tools. For a deep dive into all the differences among NoSQL databases, download our white paper, “ Top 7 Considerations When Evaluating NoSQL Databases .”

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