MongoDB 3.2.9 is out and is ready for production deployment. This release contains only fixes since 3.2.8, and is a recommended upgrade for all 3.2 users.
Fixed in this release:
- SERVER-17856 users on mongods should always be able to run currentOp and killOp on their own operations
- SERVER-23145 Shell sharding helpers should give feedback on success
- SERVER-23661 $sample takes disproportionately long time on newly created collection
- SERVER-23830 On RHEL7/Centos7 mongod can't stop if pid location in conf differs from the init.d script
- SERVER-23902 Failing to create a thread should fail with a useful error message
- SERVER-25075 Building 2dsphere index uses excessive memory
- SERVER-25500 Collection drops can cause busy applications to stall
As always, please let us know of any issues.
-- The MongoDB Team
MongoDB named a leader in The Forrester Wave™: Big Data NoSQL, Q3 2016
Today, Forrester released The Forrester Wave™: Big Data NoSQL, Q3 2016, recognizing MongoDB as a Leader based on our performance in the current offering, strategy, and market presence categories. The report said that "MongoDB remains the most popular NoSQL database." It’s always gratifying to see our efforts acknowledged, but beyond our current position as the most popular non-relational database, it is my view that this Forrester Wave report endorses our long-term strategy as clear and on-target. A little over a year ago, I concluded MongoDB World 2015 with a claim that we had entered a new era in which it was reasonable for MongoDB to be an organization's default database; I believe that this recognition shows that we’re getting there. The world is ready for a document database to be its default. 61% of the enterprises surveyed by Forrester are using, planning to use, expanding or upgrading to NoSQL over the next 12 months, and we are confident that MongoDB will continue to be the most popular choice. These enterprises have strategic needs that can only be met by a non-relational database, but they must be prudent about where they invest their fiscal and intellectual capital. They don’t want to stitch together a host of new and disparate technologies, each with its own API and narrow band of appropriate use cases, and take on work to re-implement solutions that were working fine in their relational ecosystem. We developed MongoDB with this in mind, which is why it excels at so many workloads. Our document model is a superset of other data models, including key-value, graph, object, and relational, and we natively support complex manipulations on these data with operators like $lookup and our new graph operators in 3.4. Our replication and sharding architecture, pluggable storage engine framework, and configurable read and write behavior mean that an entire spectrum of data semantics can be achieved through configuration, rather than by mixing and matching from a grab-bag of technologies. And because an unconstrained dynamic schema can sometimes be too flexible, features like document validation and tools like MongoDB Compass provide the integrity checking, schema visualization, query development and performance optimization that DBAs often miss in non-relational solutions. We are also mindful of the investment that enterprises have made in the business intelligence ecosystem that surrounds their databases. Our BI Connector allows enterprises to leverage tools like Tableau to derive insights from their data. Protecting investments in existing tools, though, doesn’t mean relying on them exclusively. We're also innovating in the next generation of analytics, machine learning, and streaming with our new MongoDB Connector for Apache Spark . Enterprises also require industrial-grade management solutions for their databases, and MongoDB has met this need with Ops Manager for on-premises management and Cloud Manager for hybrid deployments. Both of these offer monitoring, backup, and management of MongoDB clusters, making it easy to spin up a single instance to experiment with or run a massive cluster with shards spread across the globe. But these days even enterprises are starting to run their infrastructure entirely in the cloud, and we think this operational model suits a large number of teams. That is why we created our database as a service, MongoDB Atlas : the simplest, most robust, and most cost effective way to run MongoDB in the Cloud. Using Atlas, enterprises can spin up a fully managed, monitored, and backed up cluster in under five minutes. Atlas is available today on AWS, with support for Azure and GCP coming soon. Now, regardless of what type of infrastructure an enterprise wants to run, they have the flexibility to deploy and manage MongoDB with ease. After all, your data should serve you, not the other way around. We continually build and evolve MongoDB to deliver that vision, which is why MongoDB is already in use by more than half of all Fortune 100 companies. So thanks to all of our customers, users, and community contributors, for investing in us, for supporting us, for demanding more and more of MongoDB, for pushing it further, into every crazy new use case. We’re right behind you. About the Author, Eliot Horowitz Eliot is CTO and Co-Founder of MongoDB. He is one of the core MongoDB kernel committers. Previously, he was Co-Founder and CTO of ShopWiki. Eliot developed the crawling and data extraction algorithm that is the core of its innovative technology. He has quickly become one of Silicon Alley's up and coming entrepreneurs and was selected as one of BusinessWeek's Top 25 Entrepreneurs Under Age 25 nationwide in 2006. Earlier, Eliot was a software developer in the R&D group at DoubleClick (acquired by Google for $3.1 billion). Eliot received a BS in Computer Science from Brown University.
MongoDB at AWS re:Invent 2020
While 2020 has been a challenging year, it has also given rise to new levels of innovative collaboration and agile thinking. Where better to experience both than at AWS re:Invent 2020? At MongoDB, we’re excited to partner with AWS on this free, 3-week virtual event, providing unlimited access to hundreds of sessions led by Cloud experts. Although we’ll miss the grand, buzzing halls of the Venetian Hotel and the celebratory sounds of slot machines this year, it’s still important to approach AWS re:Invent with a focused plan. Think of this year’s event as an opportunity to curate your own perfectly tailored experience. Check out this page for details of our fresh new lineup of deep-dives, targeted jam sessions and — of course — the annual MongoDB late-night party. Here are some of the highlights. AWS Jam — "Excel isn't a database!" Imagine this: It's your first week in a new job, and the VP of sales has already given you an important data task. The good news? From the start of the year, all your current sales data has been stored in MongoDB Atlas — allowing operational and analytical workloads to run on the live data set. The not-so-good news? That wasn't always the case. For years before they switched, their database (well, ”database”) of choice was… Excel. Fortunately someone took the initiative to export that data in CSV format and store it in S3, but now the sales team needs your help to analyze that data — and they need it fast. In our “Excel isn’t a database!” Jam Session, you’ll test and upgrade your skills by connecting MongoDB Atlas Data Lake to CSV data that’s been languishing in an S3 bucket. Then you’ll run an aggregation to complete the challenge and claim points. Game on! This jam session will be available on-demand for the duration of AWS re:Invent Databases & S3: Auto-archiving Breakout Session Databases are built for fast access, but this can also make them resource-intensive. As data grows, you may want to optimize performance (or cost) by migrating old or infrequently used data into cheap object storage. But this presents its own problems: automating the archival process, ensuring data consistency during failures, and either querying two data stores separately or building a query federation system. In this talk, you’ll learn about how we approached these problems while building Online Archive and Federated Query features into MongoDB Atlas, lessons learned from the experience, and how you can do the same. MongoDB Late Nite That’s right: it’s a party! In the spirit of Vegas, MongoDB will be hosting an interactive late-night bash complete with throw-back entertainment at our virtual after-hours event. Like Vegas, there’s something for everyone. Unlike Vegas, the odds are actually on your side. Get your adrenaline going and dial in for exclusive swag at our Home Shopping Network. Just sign on and dial into our custom QVC-reboot every hour for a chance to snag some really cool limited-release items. Stay tuned to the event website to find out what you can win, and when! Are you a Jeopardy lover? MongoDB Late Nite is your time to shine. Exercise your mental reflexes and get those synapses firing with hundreds of other party people inside episodes of dev-focused live trivia. And what kind of revelry is complete without a resident psychic on board? Join us at the Future of Coding for an interactive reading by a VERY accurate psychic. So kick back, grab a beverage and join us at the party from home. Let’s get in the spirit together! Sponsor Page/Online Booth Pop into our virtual sponsor booth at your convenience. Our product experts will be there to answer your questions one-on-one. Alternatively, if casually exploring resources is more your style, check out our self-serve content playlists. View these to dig deeper into MongoDB education, glean customer success stories and get up to speed on the latest product features.