Closely approaching the one year mark of when I first joined MongoLab (and the MongoDB community), I had the pleasure of attending the inaugural MongoDB World conference put together by the incredible MongoDB team. Second only to the excitement around major MongoDB feature announcements was the collective disbelief that this was MongoDB’s first multi-day conference ever. A big congratulations to all those that worked hard to put on such a massive (did you see the Intrepid!?) event. All this planning would have been for naught if MongoDB leaders and engineers failed to deliver announcements and features that would meet and exceed expectations. From major public cloud announcements to the reveal of document-level locking in version 2.8, developers and conference goers had plenty to be excited about. There was a lot to digest from the conference… we’ll cover the major highlights in case you missed them. Continue Reading →
Great news, Google Cloud users!
Today Google, MongoDB Inc., and MongoLab are announcing the arrival of fully-managed, production-ready MongoDB replica set plans on the Google Cloud Platform (GCP). These plans are hosted on Google Compute Engine (GCE) and managed by MongoLab. You can get started for free!
By leveraging MongoLab’s MongoDB-as-a-Service platform on GCP, Google developers running MongoDB can focus on product development and not get bogged down by database administration and operations. Automated provisioning, multi-zone data replication, backups and monitoring are all provided by the platform, so developers only need to worry about is their schema and their code (ok, we can help you a little with that too). Continue Reading →
As developers, we often look for tools to make our work and processes more efficient. Sometimes we have to search for what we’re looking for and sometimes we’re lucky enough that it finds us! When our friends over at Treasure Data wrote to me about Fluentd, an open-source logging daemon written in Ruby that they created and maintain, I immediately saw value for MongoDB users looking for a quick way to collect data streams and store information in MongoDB.
Intro to Fluentd
Fluentd is an open source data collector designed to simplify and scale log management. Open-sourced in October 2011, it has gained traction steadily over the last 2.5 years: today, Fluentd has a thriving community of ~50 contributors and 1,900+ stargazers on GitHub with companies like Slideshare and Nintendo deploying it across hundreds of machines in production.
Most relevant to MongoDB developers, many folks use Fluentd to aggregate logs into MongoDB. The MongoDB community was one of the first to take notice of Fluentd, and the MongoDB plugin is one of the most downloaded Fluentd plugins to date. Continue Reading →
A large proportion of support requests to MongoLab are questions about how to properly configure and use a particular MongoDB driver.
This blog post is the third of a series where we are covering each of the major MongoDB drivers in depth. The driver we’ll be covering here is the PHP driver, developed and maintained by the MongoDB, Inc. team (primarily @derickr, @bjori and @jmikola). Continue Reading →
Update 5/7/14 5:15PM: Post has been rewritten to reflect Heroku’s PHP Buildpack changes
Update 5/5/14 10:45PM: Heroku’s default PHP buildpack now allows Composer to install the MongoDB extension. You do not need to use the develop branch. To enable, add “ext-mongo” to the composer.json file as described in the Solution section.
One of our close Platform-as-a-Service (PaaS) partners, Heroku, recently announced its official public beta for new PHP features. This announcement was met with much excitement from the developer community, and the MongoLab team looks forward to working with PHP developers on Heroku who want to power their apps with fully-managed MongoDB databases.
The following is a guest post by Doug Daniels, CTO of Mortar Data Inc.
Today, we’re excited to announce integration between MongoLab and Mortar, the Hadoop platform for high-scale data science. If you have one of the 100,000+ databases at MongoLab, you can now seamlessly use Hadoop to:
- Run advanced algorithms (like recommendation engines)
- Build reports that run quickly in parallel against large collections
- Join multiple collections (and outside data) together for analysis
- Store results to Google Drive, back to MongoLab, or many other destinations
In this article we’ll show you how to connect your MongoLab database to Hadoop, and then use Hadoop to do something simple but very useful: gather schema information from an entire collection, including histograms of common values, data types, and more. Mortar handles all deployment, monitoring and cluster management, so no prior knowledge of Hadoop is required. Continue Reading →
The following is a guest blog post by Brian Benz, Senior Technical Evangelist at Microsoft Open Technologies, Inc.
Since the previous release of production-ready MongoLab plans on Azure, we’ve seen demand increase significantly. The MongoLab and Microsoft teams have been working together to develop a solution for your growing requirements and are excited to announce the arrival of our newest high-memory MongoDB database plans, with virtual machine choices that now provide up to 56GB of RAM per node with availability in all eight Azure datacenters worldwide. Continue Reading →
Many of the support requests we get at MongoLab are questions about how to properly configure and use particular MongoDB drivers and client libraries.
This blog post is the 2nd of a series where we are covering the popular MongoDB drivers in depth (we covered Mongoid last time). The driver we’re covering today is Mongoose, which is maintained by Aaron Heckmann (@aaronheckmann) and officially supported by MongoDB, Inc. Continue Reading →