Monday, October 7

Tag: MongoDB Stitch

Web Tricks

Build a Slack App in 10 Minutes with MongoDB Stitch

Slack is not only the fastest growing startup in history, but it's also an app by the same name and one of the most popular communication tools in use today. We use it extensively at MongoDB to foster efficient communications between teams and across the company. We're not alone. It seems like every developer I encounter uses it in their company as well. One interesting thing about Slack (and there are many) is its extensibility. There are several ways you can extend Slack. Building chatbots, applications that interface with the communication service and extending Slack through the introduction of additional commands called "slash commands" that enable Slack users to communicate with external services. In this article, we'll build a simple slash command that enables users to store and ret...
Web Tricks

Data Enrichment with MongoDB Stitch

Objectives Here is what we are going to achieve in this tutorial: Firstly, we are going to write a document to MongoDB using MongoDB Stitch. The result in our MongoDB collection will look like this: { "_id": ObjectId("5bb27712dced5f37bebf388c"), "Title":"Guardians of the Galaxy" } Secondly, a trigger will catch this new insertion and start a function. Lastly, this function will call the OMDB external API with the given movie title, fetch data about that movie, and finally enrich our MongoDB document with the data we gathered from this API. This is the final result we expect in our MongoDB collection: { "_id": ObjectId("5bb27712dced5f37bebf388c"), "Title":"Guardians of the Galaxy", "Year":"2014", "Rated":"PG-13", "Released":"01 Aug 2014", ...
Web Tricks

​How to Integrate MongoDB Atlas and Segment using MongoDB Stitch

  It can be quite difficult tying together multiple systems, APIs, and third-party services. Recently, we faced this exact problem in-house, when we wanted to get data from Segment into MongoDB so we could take advantage of MongoDB’s native analytics capabilities and rich query language. Using some clever tools we were able to make this happen in under an hour – the first time around. While this post is detailed, the actual implementation should only take around 20 minutes. I’ll start off by introducing our cast of characters (what tools we used to do this) and then we will walk through how we went about it. The Characters To collect data from a variety of sources including mobile, web, cloud apps, and servers, developers have been turning to Segment since 2011. Segment consolid...