Alternatives to OpenStreetMap logo

Alternatives to OpenStreetMap

Google Maps, Mapbox, OpenLayers, Leaflet, and ArcGIS are the most popular alternatives and competitors to OpenStreetMap.
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What is OpenStreetMap and what are its top alternatives?

OpenStreetMap is a free, editable map of the world created by volunteers. It provides detailed, up-to-date geographic information that can be used for various purposes such as navigation, research, and urban planning. Users can contribute data, view maps offline, and create custom maps with specific features. However, OpenStreetMap may lack some of the advanced features and data accuracy found in commercial mapping services. It also requires a certain level of expertise to contribute effectively.

  1. Google Maps: Google Maps is a widely used mapping service with detailed street views, real-time traffic updates, and business listings. It offers seamless integration with other Google services, but some users may have privacy concerns due to data collection practices.
  2. Mapbox: Mapbox is a platform that allows users to design custom maps with a variety of styles and layers. It offers powerful geolocation tools and intuitive design options, but it may have a learning curve for beginners.
  3. Here Maps: Here Maps provides detailed, interactive maps for navigation, transportation, and logistics. It offers real-time traffic information and transit options, but some features are limited to certain regions.
  4. TomTom Maps: TomTom Maps offers high-quality mapping data for navigation, location-based services, and fleet management. It provides accurate traffic updates and route planning features, but it may require a subscription for full access.
  5. Bing Maps: Bing Maps is a mapping service by Microsoft that offers aerial imagery, bird's eye view, and 3D maps. It integrates well with Microsoft products, but it may have limited coverage compared to other mapping services.
  6. Leaflet: Leaflet is an open-source JavaScript library for interactive maps that can be easily customized and integrated into web applications. It is lightweight, fast, and highly customizable, but it may lack some of the advanced features found in other mapping services.
  7. MapQuest: MapQuest provides detailed maps, driving directions, and local search features. It offers customizable maps and route planning options, but it may not have the same level of data accuracy as other mapping services.
  8. ArcGIS Online: ArcGIS Online is a mapping and analysis platform by Esri that provides powerful geospatial tools for businesses and organizations. It offers advanced mapping capabilities and data visualization tools, but it may be more complex and expensive than other mapping services.
  9. CARTO: CARTO is a cloud-based mapping platform that allows users to create and share interactive maps with spatial analysis tools. It offers advanced data visualization options and location intelligence features, but it may require a subscription for full access.
  10. Citymapper: Citymapper is a navigation app that provides real-time transit information, route planning, and multimodal transportation options. It offers detailed public transportation data for major cities worldwide, but it may not have the same level of mapping detail as other services.

Top Alternatives to OpenStreetMap

  • Google Maps
    Google Maps

    Create rich applications and stunning visualisations of your data, leveraging the comprehensiveness, accuracy, and usability of Google Maps and a modern web platform that scales as you grow. ...

  • Mapbox
    Mapbox

    We make it possible to pin travel spots on Pinterest, find restaurants on Foursquare, and visualize data on GitHub. ...

  • OpenLayers
    OpenLayers

    An opensource javascript library to load, display and render maps from multiple sources on web pages. ...

  • Leaflet
    Leaflet

    Leaflet is an open source JavaScript library for mobile-friendly interactive maps. It is developed by Vladimir Agafonkin of MapBox with a team of dedicated contributors. Weighing just about 30 KB of gzipped JS code, it has all the features most developers ever need for online maps. ...

  • ArcGIS
    ArcGIS

    It is a geographic information system for working with maps and geographic information. It is used for creating and using maps, compiling geographic data, analyzing mapped information, sharing and much more. ...

  • JavaScript
    JavaScript

    JavaScript is most known as the scripting language for Web pages, but used in many non-browser environments as well such as node.js or Apache CouchDB. It is a prototype-based, multi-paradigm scripting language that is dynamic,and supports object-oriented, imperative, and functional programming styles. ...

  • Git
    Git

    Git is a free and open source distributed version control system designed to handle everything from small to very large projects with speed and efficiency. ...

  • GitHub
    GitHub

    GitHub is the best place to share code with friends, co-workers, classmates, and complete strangers. Over three million people use GitHub to build amazing things together. ...

OpenStreetMap alternatives & related posts

Google Maps logo

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Francisco Quintero
Tech Lead at Dev As Pros · | 13 upvotes · 1.6M views

For Etom, a side project. We wanted to test an idea for a future and bigger project.

What Etom does is searching places. Right now, it leverages the Google Maps API. For that, we found a React component that makes this integration easy because using Google Maps API is not possible via normal API requests.

You kind of need a map to work as a proxy between the software and Google Maps API.

We hate configuration(coming from Rails world) so also decided to use Create React App because setting up a React app, with all the toys, it's a hard job.

Thanks to all the people behind Create React App it's easier to start any React application.

We also chose a module called Reactstrap which is Bootstrap UI in React components.

An important thing in this side project(and in the bigger project plan) is to measure visitor through out the app. For that we researched and found that Keen was a good choice(very good free tier limits) and also it is very simple to setup and real simple to send data to

Slack and Trello are our defaults tools to comunicate ideas and discuss topics, so, no brainer using them as well for this project.

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Tom Klein

Google Analytics is a great tool to analyze your traffic. To debug our software and ask questions, we love to use Postman and Stack Overflow. Google Drive helps our team to share documents. We're able to build our great products through the APIs by Google Maps, CloudFlare, Stripe, PayPal, Twilio, Let's Encrypt, and TensorFlow.

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Mapbox logo

Mapbox

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    Stephen Gheysens
    Lead Solutions Engineer at Inscribe · | 7 upvotes · 462.1K views

    Google Maps lets "property owners and their authorized representatives" upload indoor maps, but this appears to lack navigation ("wayfinding").

    MappedIn is a platform and has SDKs for building indoor mapping experiences (https://www.mappedin.com/) and ESRI ArcGIS also offers some indoor mapping tools (https://www.esri.com/en-us/arcgis/indoor-gis/overview). Finally, there used to be a company called LocusLabs that is now a part of Atrius and they were often integrated into airlines' apps to provide airport maps with wayfinding (https://atrius.com/solutions/personal-experiences/personal-wayfinder/).

    I previously worked at Mapbox and while I believe that it's a great platform for building map-based experiences, they don't have any simple solutions for indoor wayfinding. If I were doing this for fun as a side-project and prioritized saving money over saving time, here is what I would do:

    • Create a graph-based dataset representing the walking paths around your university, where nodes/vertexes represent the intersections of paths, and edges represent paths (literally paths outside, hallways, short path segments that represent entering rooms). You could store this in a hosted graph-based database like Neo4j, Amazon Neptune , or Azure Cosmos DB (with its Gremlin API) and use built-in "shortest path" queries, or deploy a PostgreSQL service with pgRouting.

    • Add two properties to each edge: one property for the distance between its nodes (libraries like @turf/helpers will have a distance function if you have the latitude & longitude of each node), and another property estimating the walking time (based on the distance). Once you have these values saved in a graph-based format, you should be able to easily query and find the data representation of paths between two points.

    • At this point, you'd have the routing problem solved and it would come down to building a UI. Mapbox arguably leads the industry in developer tools for custom map experiences. You could convert your nodes/edges to GeoJSON, then either upload to Mapbox and create a Tileset to visualize the paths, or add the GeoJSON to the map on the fly.

    *You might be able to use open source routing tools like OSRM (https://github.com/Project-OSRM/osrm-backend/issues/6257) or Graphhopper (instead of a custom graph database implementation), but it would likely be more involved to maintain these services.

    See more

    Which will give a better map (better view, markers options, info window) in an Android OS app?

    Leaflet with Mapbox or Leaflet with OpenStreetMap?

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    OpenLayers logo

    OpenLayers

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    A high-performance, feature-packed library for all your mapping needs
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      Leaflet logo

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        Which will give a better map (better view, markers options, info window) in an Android OS app?

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        ArcGIS logo

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        A geographic information system for working with maps
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          Stephen Gheysens
          Lead Solutions Engineer at Inscribe · | 7 upvotes · 462.1K views

          Google Maps lets "property owners and their authorized representatives" upload indoor maps, but this appears to lack navigation ("wayfinding").

          MappedIn is a platform and has SDKs for building indoor mapping experiences (https://www.mappedin.com/) and ESRI ArcGIS also offers some indoor mapping tools (https://www.esri.com/en-us/arcgis/indoor-gis/overview). Finally, there used to be a company called LocusLabs that is now a part of Atrius and they were often integrated into airlines' apps to provide airport maps with wayfinding (https://atrius.com/solutions/personal-experiences/personal-wayfinder/).

          I previously worked at Mapbox and while I believe that it's a great platform for building map-based experiences, they don't have any simple solutions for indoor wayfinding. If I were doing this for fun as a side-project and prioritized saving money over saving time, here is what I would do:

          • Create a graph-based dataset representing the walking paths around your university, where nodes/vertexes represent the intersections of paths, and edges represent paths (literally paths outside, hallways, short path segments that represent entering rooms). You could store this in a hosted graph-based database like Neo4j, Amazon Neptune , or Azure Cosmos DB (with its Gremlin API) and use built-in "shortest path" queries, or deploy a PostgreSQL service with pgRouting.

          • Add two properties to each edge: one property for the distance between its nodes (libraries like @turf/helpers will have a distance function if you have the latitude & longitude of each node), and another property estimating the walking time (based on the distance). Once you have these values saved in a graph-based format, you should be able to easily query and find the data representation of paths between two points.

          • At this point, you'd have the routing problem solved and it would come down to building a UI. Mapbox arguably leads the industry in developer tools for custom map experiences. You could convert your nodes/edges to GeoJSON, then either upload to Mapbox and create a Tileset to visualize the paths, or add the GeoJSON to the map on the fly.

          *You might be able to use open source routing tools like OSRM (https://github.com/Project-OSRM/osrm-backend/issues/6257) or Graphhopper (instead of a custom graph database implementation), but it would likely be more involved to maintain these services.

          See more
          JavaScript logo

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          Zach Holman

          Oof. I have truly hated JavaScript for a long time. Like, for over twenty years now. Like, since the Clinton administration. It's always been a nightmare to deal with all of the aspects of that silly language.

          But wowza, things have changed. Tooling is just way, way better. I'm primarily web-oriented, and using React and Apollo together the past few years really opened my eyes to building rich apps. And I deeply apologize for using the phrase rich apps; I don't think I've ever said such Enterprisey words before.

          But yeah, things are different now. I still love Rails, and still use it for a lot of apps I build. But it's that silly rich apps phrase that's the problem. Users have way more comprehensive expectations than they did even five years ago, and the JS community does a good job at building tools and tech that tackle the problems of making heavy, complicated UI and frontend work.

          Obviously there's a lot of things happening here, so just saying "JavaScript isn't terrible" might encompass a huge amount of libraries and frameworks. But if you're like me, yeah, give things another shot- I'm somehow not hating on JavaScript anymore and... gulp... I kinda love it.

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          Conor Myhrvold
          Tech Brand Mgr, Office of CTO at Uber · | 44 upvotes · 11.1M views

          How Uber developed the open source, end-to-end distributed tracing Jaeger , now a CNCF project:

          Distributed tracing is quickly becoming a must-have component in the tools that organizations use to monitor their complex, microservice-based architectures. At Uber, our open source distributed tracing system Jaeger saw large-scale internal adoption throughout 2016, integrated into hundreds of microservices and now recording thousands of traces every second.

          Here is the story of how we got here, from investigating off-the-shelf solutions like Zipkin, to why we switched from pull to push architecture, and how distributed tracing will continue to evolve:

          https://eng.uber.com/distributed-tracing/

          (GitHub Pages : https://www.jaegertracing.io/, GitHub: https://github.com/jaegertracing/jaeger)

          Bindings/Operator: Python Java Node.js Go C++ Kubernetes JavaScript OpenShift C# Apache Spark

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          Git logo

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          • 1
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          • 1
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          Simon Reymann
          Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 9.9M views

          Our whole DevOps stack consists of the following tools:

          • GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
          • Respectively Git as revision control system
          • SourceTree as Git GUI
          • Visual Studio Code as IDE
          • CircleCI for continuous integration (automatize development process)
          • Prettier / TSLint / ESLint as code linter
          • SonarQube as quality gate
          • Docker as container management (incl. Docker Compose for multi-container application management)
          • VirtualBox for operating system simulation tests
          • Kubernetes as cluster management for docker containers
          • Heroku for deploying in test environments
          • nginx as web server (preferably used as facade server in production environment)
          • SSLMate (using OpenSSL) for certificate management
          • Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
          • PostgreSQL as preferred database system
          • Redis as preferred in-memory database/store (great for caching)

          The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:

          • Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
          • Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
          • Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
          • Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
          • Scalability: All-in-one framework for distributed systems.
          • Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
          See more
          Tymoteusz Paul
          Devops guy at X20X Development LTD · | 23 upvotes · 8.9M views

          Often enough I have to explain my way of going about setting up a CI/CD pipeline with multiple deployment platforms. Since I am a bit tired of yapping the same every single time, I've decided to write it up and share with the world this way, and send people to read it instead ;). I will explain it on "live-example" of how the Rome got built, basing that current methodology exists only of readme.md and wishes of good luck (as it usually is ;)).

          It always starts with an app, whatever it may be and reading the readmes available while Vagrant and VirtualBox is installing and updating. Following that is the first hurdle to go over - convert all the instruction/scripts into Ansible playbook(s), and only stopping when doing a clear vagrant up or vagrant reload we will have a fully working environment. As our Vagrant environment is now functional, it's time to break it! This is the moment to look for how things can be done better (too rigid/too lose versioning? Sloppy environment setup?) and replace them with the right way to do stuff, one that won't bite us in the backside. This is the point, and the best opportunity, to upcycle the existing way of doing dev environment to produce a proper, production-grade product.

          I should probably digress here for a moment and explain why. I firmly believe that the way you deploy production is the same way you should deploy develop, shy of few debugging-friendly setting. This way you avoid the discrepancy between how production work vs how development works, which almost always causes major pains in the back of the neck, and with use of proper tools should mean no more work for the developers. That's why we start with Vagrant as developer boxes should be as easy as vagrant up, but the meat of our product lies in Ansible which will do meat of the work and can be applied to almost anything: AWS, bare metal, docker, LXC, in open net, behind vpn - you name it.

          We must also give proper consideration to monitoring and logging hoovering at this point. My generic answer here is to grab Elasticsearch, Kibana, and Logstash. While for different use cases there may be better solutions, this one is well battle-tested, performs reasonably and is very easy to scale both vertically (within some limits) and horizontally. Logstash rules are easy to write and are well supported in maintenance through Ansible, which as I've mentioned earlier, are at the very core of things, and creating triggers/reports and alerts based on Elastic and Kibana is generally a breeze, including some quite complex aggregations.

          If we are happy with the state of the Ansible it's time to move on and put all those roles and playbooks to work. Namely, we need something to manage our CI/CD pipelines. For me, the choice is obvious: TeamCity. It's modern, robust and unlike most of the light-weight alternatives, it's transparent. What I mean by that is that it doesn't tell you how to do things, doesn't limit your ways to deploy, or test, or package for that matter. Instead, it provides a developer-friendly and rich playground for your pipelines. You can do most the same with Jenkins, but it has a quite dated look and feel to it, while also missing some key functionality that must be brought in via plugins (like quality REST API which comes built-in with TeamCity). It also comes with all the common-handy plugins like Slack or Apache Maven integration.

          The exact flow between CI and CD varies too greatly from one application to another to describe, so I will outline a few rules that guide me in it: 1. Make build steps as small as possible. This way when something breaks, we know exactly where, without needing to dig and root around. 2. All security credentials besides development environment must be sources from individual Vault instances. Keys to those containers should exist only on the CI/CD box and accessible by a few people (the less the better). This is pretty self-explanatory, as anything besides dev may contain sensitive data and, at times, be public-facing. Because of that appropriate security must be present. TeamCity shines in this department with excellent secrets-management. 3. Every part of the build chain shall consume and produce artifacts. If it creates nothing, it likely shouldn't be its own build. This way if any issue shows up with any environment or version, all developer has to do it is grab appropriate artifacts to reproduce the issue locally. 4. Deployment builds should be directly tied to specific Git branches/tags. This enables much easier tracking of what caused an issue, including automated identifying and tagging the author (nothing like automated regression testing!).

          Speaking of deployments, I generally try to keep it simple but also with a close eye on the wallet. Because of that, I am more than happy with AWS or another cloud provider, but also constantly peeking at the loads and do we get the value of what we are paying for. Often enough the pattern of use is not constantly erratic, but rather has a firm baseline which could be migrated away from the cloud and into bare metal boxes. That is another part where this approach strongly triumphs over the common Docker and CircleCI setup, where you are very much tied in to use cloud providers and getting out is expensive. Here to embrace bare-metal hosting all you need is a help of some container-based self-hosting software, my personal preference is with Proxmox and LXC. Following that all you must write are ansible scripts to manage hardware of Proxmox, similar way as you do for Amazon EC2 (ansible supports both greatly) and you are good to go. One does not exclude another, quite the opposite, as they can live in great synergy and cut your costs dramatically (the heavier your base load, the bigger the savings) while providing production-grade resiliency.

          See more
          GitHub logo

          GitHub

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            Easy to find projects
          • 56
            Network effect
          • 49
            Extensive API
          • 43
            Organizations
          • 42
            Branching
          • 34
            Developer Profiles
          • 32
            Git Powered Wikis
          • 30
            Great for collaboration
          • 24
            It's fun
          • 23
            Clean interface and good integrations
          • 22
            Community SDK involvement
          • 20
            Learn from others source code
          • 16
            Because: Git
          • 14
            It integrates directly with Azure
          • 10
            Standard in Open Source collab
          • 10
            Newsfeed
          • 8
            It integrates directly with Hipchat
          • 8
            Fast
          • 8
            Beautiful user experience
          • 7
            Easy to discover new code libraries
          • 6
            Smooth integration
          • 6
            Cloud SCM
          • 6
            Nice API
          • 6
            Graphs
          • 6
            Integrations
          • 6
            It's awesome
          • 5
            Quick Onboarding
          • 5
            Reliable
          • 5
            Remarkable uptime
          • 5
            CI Integration
          • 5
            Hands down best online Git service available
          • 4
            Uses GIT
          • 4
            Version Control
          • 4
            Simple but powerful
          • 4
            Unlimited Public Repos at no cost
          • 4
            Free HTML hosting
          • 4
            Security options
          • 4
            Loved by developers
          • 4
            Easy to use and collaborate with others
          • 3
            Ci
          • 3
            IAM
          • 3
            Nice to use
          • 3
            Easy deployment via SSH
          • 2
            Easy to use
          • 2
            Leads the copycats
          • 2
            All in one development service
          • 2
            Free private repos
          • 2
            Free HTML hostings
          • 2
            Easy and efficient maintainance of the projects
          • 2
            Beautiful
          • 2
            Easy source control and everything is backed up
          • 2
            IAM integration
          • 2
            Very Easy to Use
          • 2
            Good tools support
          • 2
            Issues tracker
          • 2
            Never dethroned
          • 2
            Self Hosted
          • 1
            Dasf
          • 1
            Profound
          CONS OF GITHUB
          • 54
            Owned by micrcosoft
          • 38
            Expensive for lone developers that want private repos
          • 15
            Relatively slow product/feature release cadence
          • 10
            API scoping could be better
          • 9
            Only 3 collaborators for private repos
          • 4
            Limited featureset for issue management
          • 3
            Does not have a graph for showing history like git lens
          • 2
            GitHub Packages does not support SNAPSHOT versions
          • 1
            No multilingual interface
          • 1
            Takes a long time to commit
          • 1
            Expensive

          related GitHub posts

          Johnny Bell

          I was building a personal project that I needed to store items in a real time database. I am more comfortable with my Frontend skills than my backend so I didn't want to spend time building out anything in Ruby or Go.

          I stumbled on Firebase by #Google, and it was really all I needed. It had realtime data, an area for storing file uploads and best of all for the amount of data I needed it was free!

          I built out my application using tools I was familiar with, React for the framework, Redux.js to manage my state across components, and styled-components for the styling.

          Now as this was a project I was just working on in my free time for fun I didn't really want to pay for hosting. I did some research and I found Netlify. I had actually seen them at #ReactRally the year before and deployed a Gatsby site to Netlify already.

          Netlify was very easy to setup and link to my GitHub account you select a repo and pretty much with very little configuration you have a live site that will deploy every time you push to master.

          With the selection of these tools I was able to build out my application, connect it to a realtime database, and deploy to a live environment all with $0 spent.

          If you're looking to build out a small app I suggest giving these tools a go as you can get your idea out into the real world for absolutely no cost.

          See more

          Context: I wanted to create an end to end IoT data pipeline simulation in Google Cloud IoT Core and other GCP services. I never touched Terraform meaningfully until working on this project, and it's one of the best explorations in my development career. The documentation and syntax is incredibly human-readable and friendly. I'm used to building infrastructure through the google apis via Python , but I'm so glad past Sung did not make that decision. I was tempted to use Google Cloud Deployment Manager, but the templates were a bit convoluted by first impression. I'm glad past Sung did not make this decision either.

          Solution: Leveraging Google Cloud Build Google Cloud Run Google Cloud Bigtable Google BigQuery Google Cloud Storage Google Compute Engine along with some other fun tools, I can deploy over 40 GCP resources using Terraform!

          Check Out My Architecture: CLICK ME

          Check out the GitHub repo attached

          See more