This blog was written by Aaron Cox who holds the position of Manager of Software Product Development at DataServ.
DataServ is a SaaS ECM company that provides accounts payable, accounts receivable, and human resources automation solutions to clients worldwide and has been doing so since 1994. Our solutions improve controls, save money, and increase user satisfaction and performance by eliminating paper, automating workflow, and providing instant access to document images, either in our platform or through a client’s Enterprise Resource Planning (ERP) system. All of our document images and data are integrated into our workflow automation solutions, which are... Read More >
When we last left off in our MongoDB vs SQL blog series, we covered Day 1 and Day 2 of building the same application using MongoDB vs using SQL with code comparisons. Before we jump into the next couple of days, let’s go over the ground rules again:
We’ll be using Java
Assume we have a data access layer in between our application and MongoDB
In terms of the date counts as we go through the examples, just treat them as progress indicators and not the actual time needed to complete the specified task.
Ah, but a man's reach should exceed his grasp, Or what's a heaven for? -- Robert Browning, "Andrea del Sarto"
I’ve always been fascinated by questions of scalability. Working for then-leading enterprise search vendor Verity around 2005, we developed a sub-specialty implementing text search applications for our largest customers. Anything over 30 million documents stretched the already obsolescent Verity engine to its limits. Such implementations were clearly a level beyond mere “enterprise scale,” and there was no common term for larger problems, so we started referring to them as “empire scale.”
This will be the first post in an ongoing series based on our popular webinar about the differences in building an application using SQL versus building the same application using MongoDB.
First off - before we get into anything - what is it that we’re all trying to achieve with our data? Sure, there are necessary evils such as reading and writing data from databases, putting data on message buses, and working through open source integrations, but at the end of the day what we really want to do is take information, compute it, and get it in... Read More >
GameChanger has taken amateur sports teams (e.g. Little League) into the digital era. Their mobile app and website provide scorekeeping, stats and team management for the coaching staff, and live game updates, stats and recap stories for families and fans.
The relational database has been the foundation of enterprise applications for decades, and MySQL has been one of the most popular and inexpensive options available. But with the explosion of unstructured data, new databases like MongoDB have emerged to address the requirements that modern applications demand. You need a new kind of database in order to manage, process, and analyze data that doesn't fit into the neat rows and columns of a relational table.
Choice is a good thing, but it can add complication, especially when there are now so many different database technologies to choose from. Yet it doesn't... Read More >
On Monday I had the pleasure of participating in the Big Data Panel at TIBCO NOW, a leading technology conference focused on exploring disruptive technological forces like Big Data, Cloud, Mobile, and Social. Here are a few of my key takeaways from the discussion...Read More >
We’re excited to announce a concerted effort to grow our Global Consulting Services, led by Vijay Vijayasankar, VP and GM of Global Channels and Consulting Services. Vijay has more than 14 years of experience leading consulting teams for a wide variety of enterprises across North America, Europe and Asia.Read More >
The connector, which allows customers to use MongoDB as an input source and/or output destination for Hadoop deployments, is now certified on distributions from all of the leading vendors in the space, including MapR, Hortonworks, and Cloudera.Read More >
This is a guest post by ObjectLabs Corporation/MongoLab. MongoLab is a partner of MongoDB, Inc. and not directly affiliated with the company.
If you are looking to run your application with MongoDB on Google Compute Engine, you may already be familiar with Google’s many powerful features that make it great for hosting your infrastructure: quick virtual machine (VM) spin-up time, incredibly fast networking, and live VM migrations.
At MongoLab, we offer our customers a fully-managed Database-as-a-Service platform that abstracts away the lower-level infrastructure layer and lets developers manage multi-node MongoDB clusters with ease. And we’ve partnered with all of the... Read More >