The bottom line: If you're building a tool to map jobs within commute range, TravelTime's specialized APIs will save you time, money, and headaches compared to Google Maps—especially for public transit and realistic commute estimates.
When workers need to find manufacturing jobs within a reasonable commute, the mapping tool you choose makes all the difference.
After building commute-mapping features with both Google Maps and TravelTime, one clear winner emerged for this specific use case.
While Google Maps seems like the obvious choice, TravelTime's purpose-built commute analysis tools provide better accuracy, more realistic transit estimates, and simpler implementation for showing workers exactly where they can realistically travel for work.
Understanding Data Needs and Sources
I want to map manufacturing jobs that are available within a 30-minute commute of a given address. What tools do I need, and what do I reach for first?
I'll need two data sources: job data and mapping data. Getting job data is not a hard problem to solve - we just want a structured file with enough data to know an address or coordinate for each job.
The file format doesn't matter very much, as long as we have the needed fields. It would be wonderful if shift times were provided, but job listings are rarely that clear.
The mapping data is more difficult because we'll depend on a source of traffic data. That gets complex:
- How am I commuting? Am I driving? Taking the bus? Walking? Some combination (multi-modal commute)?
- If I am taking the bus, how much am I willing to walk on either end of the route?
- What time of day is it? I can't get as far, as fast, driving during rush hour. Bus routes also only operate at certain times throughout the day.
Google Maps
As a developer, it's easy to reach for the biggest box on the shelf with a familiar name and just run with it. Google Maps is an obvious starting point: it has a lot of available data and a lot of documentation about how to mine it.
Distance Matrices and Cost
We can do a lot with Google Maps. We can pin jobs on the map based on locations and run a distance matrix to determine the commute duration between sets of points.
Given a home address, I can know what jobs are within a certain range. That matrix is flexible depending on the time that I want to leave home or arrive at work.
But Google Maps has drawbacks. Do I run the distance matrix for every address that I need to see? That cost would start to add up.
Isochrones
What if I want to see an isochrone, or a shape representing the complete area within that 30-minute commute, so I can more easily assess why jobs are inside or outside that area? Google Maps doesn't have one easily available.
It is possible, but you have to do a lot of work to get there by computing distances between points down to a particular resolution to set up a usable shape.
For instance, we could break the map down into something granular, like census tracts or census blocks, compute all of the travel durations, and map the shapes. It’s doable, but the more granular we get, the number of requests (which we pay for) goes up exponentially.
Commute Wait Time
If I'm taking the bus from home to work, and I tell Google Maps to give me a commute time for arriving at work for an 8 am shift, it might tell me it's a 30-minute commute. But it won't tell me what time the bus arrives and how long I’ll have to wait to start my shift when I get there.
That 30-minute commute might have me arriving at 6 am based on a certain bus route, and I would be left waiting two hours to start. That waiting time doesn't get counted as part of the commute.
TravelTime
A UK-based company, TravelTime specializes in solving commute duration problems. As we look at Google Maps’ drawbacks, let's see how TravelTime stacks up.
Distance Matrices and Cost
TravelTime has flat monthly or annual billing. At a certain volume of requests, that tips the balance away from Google Maps. The potential drawback here is the rate limits for requests per minute, so the need must be balanced with the budget.
The cost differential can quickly become apparent. If I want to calculate a public transit distance matrix at the census block level, a good-sized city could have 20,000 blocks or more just within range of the transit routes and stops. We'd need to square the number of blocks for the number of elements in the matrix (400 million).
When pricing is in blocks of 1,000 elements, you can see how quickly that adds up. Other options for computing distance matrices exist, but most of them do not have time-aware public transit data available.
Isochrones
TravelTime provides these shapes for us, saving a lot of the distance matrix work (although the matrix is quite useful for other scenarios). These shapes can be calculated for both departure times and arrival times.
Commute Wait Time
Unlike Google Maps, TravelTime includes the wait time in the duration. From my example above, if I'm traveling 30 minutes by bus that arrives 2 hours early, the duration would be 2.5 hours.
Real-World Expectations and Accuracy
An interesting aside: TravelTime's isochrones were almost universally smaller than the Google Maps samples we computed. In other words, particularly for public transit data, Google Maps was more optimistic about how far you could get on a bus within a given duration.
In real-world usage, where we want to give workers realistic estimates of commute times, the odds are against a highly efficient travel experience. It's more likely that things will happen that slow the commute down, so a more conservative route duration makes sense.
Real Application of TravelTime
TravelTime was a much better fit for our original premise and greatly simplified the approach:
- Give me an isochrone shape for a commute from a given address.
- Then, do some GIS computation to see which points are inside that shape.
- If my job records are already in a database with GIS capabilities (e.g., PostGIS), most of my work is done.
Then, on the presentation side, we end up with a high-resolution shape to show the commute area that we can pair with our job points.
We have an isochrone layer on our maps that grades the shapes in shades for 30, 60, or 90-minute patterns. We've also worked on the distance matrix to support searching data within a desired commute range.
Their communication and support have been top-notch throughout the process, and I would recommend their service for commute-mapping needs.
Isochrone comparison, basic shapes - TravelTime on the left, limited approximation from Google Maps on the right
More advanced isochrone shapes with other mapping features
Making the Right Choice for Your Project
For developers building commute-mapping tools, the choice between Google Maps and TravelTime comes down to your specific needs and scale.
Google Maps works fine for simple, low-volume distance calculations, but TravelTime excels when you need realistic commute estimates, especially for public transit users who need accurate commute times.
The ready-made isochrone shapes alone justify TravelTime's use for most commute-mapping projects.
Instead of building complex workarounds to approximate commute areas, you get accurate, time-aware shapes that reflect real transit schedules and wait times.
For manufacturing workers who depend on reliable public transit to get to shift work, that accuracy translates directly into better job matches and more realistic expectations.
If you're building tools to help people find work within their commute range, start with TravelTime. Your users, and your development timeline, will thank you.