Invite Your Boss to the Business Track at MongoNYC

Meghan Gill
May 23, 2013 | Updated: May 22, 2015
#mongodb days

MongoDB Days have traditionally been focused on the developer community, with lots of technical talks on application design, deployment best practices, and ops war stories. MongoNYC will carry on the tradition of including many deep technical sessions, with talks from the 10gen staff on the latest features in 2.4, as well as presentations from MongoDB community members on their experiences deploying MongoDB in real-world scenarios.

But this year at MongoNYC, we’re introducing a new track aimed at IT managers, directors, and C-level executives who aren’t knee-deep in code. The business track will include case studies from 10gen customers with a focus on the business benefits of using MongoDB, such as reduced cost, new revenue streams and competitive advantaged. We’ll look at the steps enterprises take to adopt NoSQL and open-source technologies, and how you can learn from their experiences.

Here are some of the talks included on the business track at MongoDB NYC:

  • Telefonica explains how it reduced development time by over 80% from its previous Oracle implementation, building a rich, globally available user data management system.

  • ADP describes how it built a mobile app in just a few months to let customers view payroll and benefits information on their devices of choice, differentiating ADP from stale on-premise solutions.

  • Criteo shows how it supported 200,000% growth over five years and global expansion to 7 continents migrating away from SQL Server to MongoDB for its core business, improving online shopping by bringing the performance of search to display advertisers.

  • And more.

So if you’re a developer or DBA who loves MongoDB, but you’ve only been able to use it for small or side projects, consider inviting your boss to MongoNYC this year. Or, attend the business track and return to the office as an advocate for the business advantages of MongoDB in your enterprise.

For more information on MongoDB NYC or to register, please visit http://www.10gen.com/events/mongonyc-2013. Tomorrow is your last chance to register at the early bird rate, which is only $75. Looking forward to seeing you there.

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New Geo Features in MongoDB 2.4

Motivation Geometric processing as a field of study has many applications, and has resulted in lots of research, and powerful tools. Many modern web applications have location based components, and require a data storage engines capable of managing geometric information. Typically this requires the introduction of an additional storage engine into your infrastructure, which can be a time consuming and expensive operation. MongoDB has a set of geometric storage and search features . The MongoDB 2.4 release brought several improvements to MongoDB’s existing geo capabilities and the introduction of the 2dsphere index . The primary conceptual difference (though there are also many functional differences) between the 2d and 2dsphere indexes, is the type of coordinate system that they consider. Planar coordinate systems are useful for certain applications, and can serve as a simplifying approximation of spherical coordinates. As you consider larger geometries, or consider geometries near the meridians and poles however, the requirement to use proper spherical coordinates becomes important. In addition to this major conceptional difference, there are also significant functional differences, which are outlined in some depth in the Geospatial Indexes and Queries section of the MongoDB documentation. This post will discuss the new features that have been added in the 2.4 release. What’s New Storing non-point geometries Unlike the 2d index, which only allowed the storage of points, the 2dsphere index allows the storage and querying of points, lines, and polygons. To support the storage of different geometries, instead of introducing a proprietary format, MongoDB conforms to the GeoJSON standard. GeoJSON is a collaborative community project that produced a specification for encoding entities in JSON. It has garnered significant support, including the OpenLayers project , PostGIS , and has growing language support for python and ruby . Here are a few simple examples of GeoJSON embedded documents: A BSON Document with a GeoJSON Point embedded in the geo field: { geo: { type: “Point”, coordinates: [100.0, 0.0] } } A BSON Document with a GeoJSON LineString embedded in the geo field: { geo: { type: “LineString”, coordinates: [ [100.0, 0.0], [101.0, 1.0] ] } } A BSON Document with a GeoJSON Polygon embedded in the geo field: { geo: { type: “Polygon”, coordinates: [ [ [100.0, 0.0], [101.0, 0.0], [101.0, 1.0], [100.0, 1.0], [100.0, 0.0] ] ] } } Note: A GeoJSON Polygon’s coordinates are an array of arrays of point specifications. Each array of point specifications should have the same starting and ending point to form a closed loop. The first array of point specifications defines the polygon’s exterior geometry, and each subsequent array of point specifications defines a “hole” in the polygon. Polygons should be non self-intersecting, and holes should be fully contained by the polygon. Inclusion searches on a sphere The new $geoWithin operator, which takes a Polygon geometry as a specifier, returns any geometries of any type that are fully contained within the polygon. It will work well without any index, but must look at every document in the collection to do so. Intersecting geometries on a sphere The new $geoIntersects operator, which takes any geometry as a specifier, returns any geometries that have a non-empty intersection with the specifier. $geoIntersects also works well without an index, and must also look at each document in the collection. Better support for compound indexes The 2d index can only be used in a compound index if 1. it is the first field, 2. there are exactly two fields in the compound index, and 3. if the second field isn’t a 2d index. 2dsphere indexes aren’t limited in this way, which allows us to pre-filter based on a non-geo field - which is often more efficient. Consider the following queries: Find me Hot Dog Stands in New York state i.e. use a compound index: (business_type, location). Find me geometries in New York state that are Hot Dog stands i.e. use the compound index: (location, business_type) The first query will be much more efficient than the second, because business_type is a simple text field, and greatly reduces the set of geometries to search. Additionally, we can have multiple 2dsphere indexes in the same compound index. This allows queries like: “Find routes with a start location within 50 miles from JFK, and an end location within 100 miles of YYC”. How it Works Everything starts when you insert a geometry into a 2dsphere index. We use the open source s2  C++ library  from google to select a minimal set of cells that fully cover a geometry. This set of grid cells is called a covering, and the size of the cells is dynamic (between 500m and 100km on a side) based upon the size of the polygon being covered. fig 3 - A very low granularity covering of the entire United Kingdom fig 4 - A fairly granular covering of the A4 around Trafalgar Square.  Each cell in these coverings is now added to a standard B-tree index, with a key that is easily calculable by the location on surface of the sphere - more granular(smaller) cells will have the same prefix as a larger cell that occupies the same area of the surface of the sphere. Intersection & Within searches Finding geometries that may be intersecting or within a search polygon becomes as easy as generating a covering for the search specifier, and for each cell in that covering, query the B-tree for any geometries that interact with these cells. Once the list of possibly interacting geometries has been retrieved from the index, each geometry in checked in turn to see if it should be included in the result set. Near searches The near search provided by the $near operator is implemented by doing $within searches on concentrically growing donuts (circular polygons with with circular holes).   We encourage user feedback and testing on these new Geo features and are excited to see what the community builds. Map images ⓒ  OpenStreetMap  contributors, licensed under the Creative  Commons Attribution-ShareAlike 2.0  license (CC-BY-SA).  Map data ⓒ  OpenStreetMap  contributors, licensed under the  Open Data Commons Open Database License  (ODbL).

May 21, 2013
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How the Austin Chapter of MongoDB’s Women’s Group Built Community During the Pandemic

MongoDB is on a mission to create an inclusive workplace where every single employee can thrive. With a range of established affinity groups — and new ones forming regularly — MongoDB looks for ways to amplify those groups’ efforts and help support their overall mission. When the COVID-19 pandemic forced offices to shut down and employees to work from home, our affinity groups were challenged to find creative ways to support and grow their now-remote communities. As leaders of the MongoDB Women’s Group Austin chapter, we share how we pivoted this challenge into an opportunity. First, What's the MongoDB Women's Group The MongoDB Women’s Group is a community of MongoDB employees identifying as women, nonbinary, or trans. Our mission is to create a bold, visible, and united force for gender equality. To help us get there, the MongoDB Women’s Group hosts monthly members-only meetings as well as events open to both members and allies. Relaunched in 2018, the Austin-based chapter connects women and allies in our Austin office to a community of local companies and women’s groups that can support their growth within the tech industry. Pre-COVID, we gained a lot of momentum with our events, which included a live speaker series in the office, yoga, and events focused on subjects such as fertility and imposter syndrome. When COVID-19 hit, we faced a new challenge: how do we create a sense of community for our members when everyone works completely remote? Although initially daunting, the challenge of organizing remote events was an opportunity in disguise. It enabled us to kick off a speaker series for all employees, featuring prominent women in leadership positions across the country. Enter Angie Brown, from The Home Depot. Angie was the first woman to join our remote speaker series, and we couldn’t have asked for a better person to kick it off. She began her career at The Home Depot in 1998 as an entry-level software developer and now is Vice President of Technology — Merchandising, leading a team that develops solutions to support cataloging, pricing, and assortment capabilities at the giant retail chain. She also helps to mentor aspiring leaders in a number of ways, including actively participating in Atlanta’s Women in Technology association. Here, we share some highlights from our fireside chat with Angie during which she discussed her career and provided advice on what women can do to set themselves up for success. Fireside Chat with Angie Brown MongoDB: What advice do you have for those just starting off in their careers? Angie Brown: Opportunities can look like problems and not everyone wants to run into the fire, but avoiding problems can really be a missed opportunity. That’s one important lesson I’ve learned throughout my career. Although you should have a general idea of where you want to go, you also need to be willing to flex. Things might unfold in ways you didn’t expect. If you’re too prescriptive, you might miss out on them. So, you need to find a way to strike a balance. MongoDB: You took a role in leadership fairly early. How did you change your skills and evolve as you moved up? AB: When I talk to people considering moving into management, I ask them to look at the job and determine if the required qualities and responsibilities would make them happy. It’s not just about the title and pay increase. When you pivot from being an individual contributor to being in a leadership role, servant leadership is a huge part of it. If you look at management as a way to control, you won’t be happy. If you look at it as a way to serve others and help them be successful, then you’ll find joy in that career shift. I didn’t prethink this when I first moved into management and had a little bit of an identity crisis. I was used to being the one who got things done. All of a sudden, my role and life was all about going to meetings, and I didn’t look at meetings as tangible work. I was over it. Where was the joy in this? If your joy comes from having your hands on the keyboard and needing to do things your way, then being in management would be like fitting a square peg in a round hole. At first I felt invalidated and unsure of myself because it wasn’t my hands on the keyboard. I had to work through that and do a little soul-searching. I reframed my thinking to be happy leading a team and helping them solve their problems, even if it meant I wasn’t solving them myself. I had a lightbulb moment when I moved into a director role when I realized I was still solving big problems by helping my team tackle them. There’s nothing wrong with where you find your joy and no judgement if your passion aligns as an individual contributor; we need amazing developers! Always be aware of the work itself and make sure it aligns with what you enjoy. MongoDB: How have mentors played a role in your success? AB: I wish I had invested in mentors much sooner. In the early stages of my career, I didn’t think I needed help and believed I could just figure it all out on my own. I thought asking for help was a sign of weakness. In hindsight, my mentors have absolutely formed part of who I am today. I don’t have just one mentor. Instead, I look at a topic and focus on finding a mentor for that specific topic. With that approach, I have ended up having a number of mentors. Thank you again to Angie Brown! We appreciate your insight and inspiration. If you are interested in joining MongoDB, explore our career opportunities and join an innovative team that is disrupting the database industry every day.

November 30, 2020