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Database of all buildings in Singapore with postal codes

The database contains EVERY searchable item on OneMap.sg, including HDB blocks, condominiums, landed houses, commercial, office and industrial buildings, schools, places of worship, gas stations, parks, MRT stations, and few more. Data included is building name, address, street name, postal code, GPS latitude and longitude, X and Y coordinates, etc. But also building type, since May 2021 update onward.

Download SAMPLE:
Singapore-Buildings-Database-SAMPLE.xlsx

Buy FULL database + FREE updates for 1 year:

Contact me for partial purchases (specific postal districts if you don’t need whole Singapore)

Use below map + video to prove level of completeness

Building type contains 140 different values. ZeeMaps offer 31 pins colors and I am yet to decide how to use them. Feel free to suggest changes.

Red are HDB buildings
Yellow and orange are various types of landed housing
Green are private apartments and condominiums
Blue are commercial buildings
Pink are industrial buildings
White are buildings yet to be classified

Terms of use according https://www.onemap.sg/legal/opendatalicence.html
You can use, access, download, copy, distribute, transmit, modify and adapt the datasets, or any derived analyses or applications, whether commercially or non-commercially.

However, because took some time to code scraper and several days of running computer 24/7 to get all data, you are not allowed to distribute or resell my database. You are allowed to use it in your company. If a friend or another company wants to use same data, tell them to buy from me.

History & list of updates

The database is raw data scraping from OneMap.sg and the map’s raw data does NOT indicated building type. Several people asked me for building type, but checking map to identify building types would be a manual job taking few dozens hours of manual work, once completed I will sell database at double price. But before investing any more effort in this database I need to secure future updates.

One of my customers who bought HDB Database and Condo Database in August 2017, made a scraping software to get buildings information from OneMap.sg and gave me the CSV data dump (141099 buildings) as “work exchange”, with permission to resell on my website. He did not gave me the scraper, but only data, gave me an update in January 2018 (120508 buildings), I suspected that he missed lots of postal codes, I emailed him to run scraper again, I emailed a week later and he replied that did not had time to run again, and after this he never replied me anymore.

While looking for someone to give me the scraper so I can update database myself in the future, in 2018 someone claimed that building type can also be added automatically (how?) but we did not agreed on price of initial scraper, he no longer want to work with me. In November 2018 an Indian helped me updating Python scraper to work with current version of OneMap, but the script don’t work at my computer for unknown reasons (in his computer it works fine, proved via TeamViewer).

July 2019: I found another Indian to fix and run the script, got 141754 buildings. The difference of about 20,000 buildings is because a of couple of entries share same postal code.

March 2020: 141726 buildings.

1 May 2021: 141958 buildings. Added building type, thanks to a Python programmer from Egypt who also figured out a way to add building type. Now I have a WORKING scraper that I can run on my computer and update anytime.

December 2021: 142696 buildings.

3 March 2022: 142879 buildings.

1 October 2022: 142927 buildings.

5 thoughts on “Database of all buildings in Singapore with postal codes”

    1. The only option is to buy entire database at $700, I have not added yet building type tag to be able to filter and sell you only residential buildings (I assume that 75% of buildings in database are residential).

      I still hope to find someone else able to help me able to add building type tag, either manually, either find a way to automatize it, so I won’t need to spend 100 hours of my personal time on this project and focus on more profitable projects such as https://www.teoalida.com/cardatabase

      1. Many thanks to Mido, a programmer experienced in Python helped me to enhance Singapore Buildings Database with building type in a couple of hours of coding, he saved me from spending 100 hours doing this job manually, and he was not too expensive.

  1. Database of all buildings in Singapore with postal codes is so amazing and adoring post for all the new generations to having their best criteria’s in Pakistan to having the most grateful and obedient Essay writing services very easily from them.

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