Speed up your geocoding

The problem

You need to geocode many locations quickly.


Before we begin, it's important to understand what happens when you make an API request. Basically:

  1. Your request leaves your computer and crosses the internet to our servers.
  2. Our software answers the request.
  3. Our servers send the answer back to you, across the internet.

As you can imagine, the length of time for steps 1 and 3 will depend on where you are on the internet.

Batch or Bulk geocoding

One idea that often comes up is to send multiple locations per request, or to send a file full of locations that can be processed and then be downloaded after all locations are geocoded. This is often referred to as "batch" or "bulk" geocoding.

We intentionally don’t support more than one location per request as our (hard-earned) experience is that the conceptually much simpler "one location, one request" model is much less likely to lead to misunderstandings or errors of implementation, thus saving engineering time, which is the most valuable resource for almost all of our customers.



First of all, the fastest request is the one you don't make. Unlike with many geocoding services that are built on non-open data, you can store our results as long as you like, whether you are a customer or not. Can you do more caching to reduce the number of requests you need to send us?

Do not use a proxy or VPN

If possible ensure your requests are coming directly to our servers, rather than redirecting via a proxy.

Requesting in parallel rather than in series

Assuming that you looked in your cache, and decided that you do need to make an API request, the way to churn through your dataset quickly is to send many requests in parallel (at the same time) rather than in series (one after another). This option is not available to free trial users who are limited to one request per second. Paying customers can send us many more requests per second (you can see the exact numbers on our pricing page). How you run requests in parallel will depend on the programming language you are using, but essentially it is as simple as having multiple services running at the same time.

We have customers geocoding millions of locations per day, requesting in parallel works.

We have example scripts for making parallel requests in Python (see the "Running many parallel queries" section of our tutorial), Node.js, Ruby, and PHP.

Speeding up individual requests

Nevertheless, there are several things you can do to help us answer your request more quickly (Step 2 in the list above).
  • Do you need the information in our annotations? If not adding the optional parameter no_annotations=1 will skip that step and let us respond slightly more quickly. It also reduces the size of the response considerably (and thus reduces the amount of information we need to send back to you).
  • Please do everything you can to obey our best practices. Especially the forward geocoding query formatting guide. In general, the longer your query, the longer it will take us to respond.
  • We cache forward geocoding requests, unless you have specified no_record=1 So it may be slightly faster if you don't use that optional parameter, though it will depend on how common your requests are.
  • Finally, turning pretty printing off, ie NOT using pretty=1 marginally reduces the response size.

All that being said, generating the response is typically very fast, almost always the bulk of the time is spent in crossing the internet (Steps 1 and 3 above). Our servers are at redundant locations in Germany and are well connected to the major networks. Nevertheless, there is no escaping the fact that a request from the US west coast - for example - has to cross the Atlantic twice.

Our server performance in independently monitored by StatusCake. You can see how we are doing here.

Happy geocoding!

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