4 results

Learn more about MongoDB Monitoring Service (MMS)

If you've already deployed an application using MongoDB, you might have heard about MongoDB Monitoring Service (MMS) , a free and publicly available SaaS solution for monitoring your MongoDB deployment. On Thursday, February 9, 10gen's Jared Rosoff will host a free webinar, Monitoring Your MongoDB Deployment . The webinar includes an MMS demo and will give MongoDB users the chance to ask questions about deploying and maintaining applications based on the NoSQL database. MMS is a secure system which collects usage statistics and allows users to proactively monitor a MongoDB cluster via a simple Python agent. The data collected is sent securely to the centralized MMS servers for storage and presentation; at-a-glance charts and automated alerts make it easy to keep your application running smoothly. MMS is custom-built, which means it takes into consideration the unique requirements of MongoDB. Unlike most off-the-shelf monitoring systems, which are built for generic systems management, MMS embodies the best practices for MongoDB by incorporating wisdom from 10gen engineers who have worked with hundreds of production deployments. Performance, resource utilization, availability, and response times are all tracked on the custom MMS interface. If you've already purchased a support package from 10gen, MMS allows our team of engineers to provide superior customer support by proactively monitoring the health of your deployment. In some cases, 10gen engineers identify potential issues before they pose a serious threat. We understand the sensitive nature of MMS data and have extensive data access controls and audits in place. Setup and configuration of MMS is simple—within minutes of installation, your devops and systems administration team can manage and optimize your MongoDB deployment, and derive valuable insights from key operational metrics. Just create an account at , then download and install the agent on your MongoDB cluster. Within a few minutes, your data will be visible on the web-based platform. Learn more about MMS today or get started with MMS now. Tagged with: 10gen, database, free webinar, mongodb, nosql, MMS, MongoDB Monitoring Service

January 27, 2012

MongoDB Case Study: Wordnik

At six times the size of the Oxford English Dictionary, Wordnik helps bring words to life by showing the conversations happening around them. Because Wordnik relies on data from real-time web posts, they needed a reliable and performance-tested database solution. In 2009, Wordnik engineers realized that their existing MySQL data store couldn't keep pace with the user-generated content which constantly expanded the site's dictionary. The engineers created a prototype to test MongoDB, migrating five billion records to the non-relational database in a single day. Over the course of the next month, the entire database was migrated to MongoDB under the watchful eyes of a single developer. MongoDB now handles every site request sent to Wordnik—often over 20 million API calls per day, from millions of unique users each month. Under their previous MySQL system, Wordnik's IT engineers frequently dealt with locked tables and outages when too much data was added at once; using MongoDB as a non-relational database solution has eliminated the problem, and the system handles bursts of as many as 50,000 words per second during busy periods without breaking a sweat. For Wordnik's engineers, life with MongoDB has meant faster data retrieval and 75% less code. To read more about how Wordnik has deployed MongoDB (and how it changed day-to-day life for developers), visit the full-length case study , or check out Wordnik VP of Engineering Tony Tam's presentation at MongoSV 2011. Tagged with: mongodb, 10gen, wordnik, nosql, database, data store

December 22, 2011

There are now three separate categories of DBMS: relational, business intelligence, and NoSQL

We can't know where we're going unless we know where we're from. In that spirit, here's our take on the still-ongoing evolution of the database software space. There used to be two main categories of database management systems (DBMS). One was the classic operational relational database management system like Oracle or the open source MySQL. The other was the business intelligence database space. Products in this category are SQL, but the difference is that they're for data warehousing and support - they're not designed to be real time operational stores. Think of offline, background data processing and mining with decision support and intelligence. Examples that come to mind are Vertica, Aster Data, Greenplum, and Netezza. In this business intelligence database bucket, we’d also include technologies like Hadoop, that are more data processing than storage but directly adjacent to DBMS. That was the old world. It's safe to say in 2010 that the first bucket, operational databases, has split in two, creating three separate categories of DBMS. It's not going to be just all Oracle and MySQL. Some use cases will still be, but we’d bet at least half of the operational use cases are going to end up on the new breed of solutions called NoSQL in the next couple years. The advantages of NoSQL databases are no secret at this point - high horizontal scalability (crucial in a time when cloud computing is becoming immensely popular), performance, and ease of assembly for developers working with agile techniques and object-oriented programming languages. Forward-looking organizations will have to come to terms with this disruption in the DBMS market. As more and more data subsystems require the unique benefits that NoSQL offers, more developers and businesses will jump on the bandwagon. MongoDB has started to set this trend with users like SourceForge, GitHub, the New York Times and Electronic Arts. A possible analogy is the move from procedural to object-oriented programming. You won't want to be the last person to write a web app using NoSQL, just as 20 years ago, you didn't want to be the last person to pick up object-oriented programming. Tagged with: nosql, database, business intelligence

February 1, 2010