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Enterprise Landscape By SMEs And Non-SMEs, Annual

Data from Jan 2010 to Dec 2025

Last updated: 13 May 2026, 20:00 SGT

SINGSTAT (Singapore Department of Statistics)

Source: SINGAPORE DEPARTMENT OF STATISTICS

Data Last Updated: 30/03/2026

Update Frequency: Annual

Footnotes: 1. Enterprises include incorporated or registered entities (such as company, sole-proprietorship, partnership, association or society, etc) and has revenue or employment in the reference period. Ministries, statutory boards, and government/government-aided schools are also included. 2. SMEs (i.e. Small & Medium Enterprises), are defined as enterprises with operating revenue not more than $100mil or employment not more than 200 workers. 3. Non-SMEs are defined as enterprises with operating revenue more than $100mil and employment more than 200 workers. It also includes ministries, statutory boards, and government / government-aided schools. 4. Employment of enterprises refers to total employment excluding migrant domestic workers, own-account workers and contributing family workers. 5. Value-added of enterprises refers to Gross Value Added (GVA) less ownership of dwellings.

Adapted from: https://tablebuilder.singstat.gov.sg/table/TS/M600981

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Sample OpenAPI query

This code can be used to test a sample API query. It retrieves the data catalogue of this dataset. For a complete guide on query parameters and syntax, please refer to the API documentation. Try it out on your browser to see the response schema.

import requests
          
dataset_id = "d_f9c93c1ffcefe660272c101cd733711c"
url = "https://data.gov.sg/api/action/datastore_search?resource_id="  + dataset_id 
        
response = requests.get(url)
print(response.json())

Data explorer

EnterpriseLandscapeBySMEsAndNonSMEsAnnual.csv (18 rows, 2.3 KB)

Data Series Text	2025 Numeric	2024 Numeric	2023 Numeric	2022 Numeric	2021 Numeric	2020 Numeric	2019 Numeric	2018 Numeric	2017 Numeric	2016 Numeric	2015 Numeric	2014 Numeric	2013 Numeric	2012 Numeric	2011 Numeric	2010 Numeric
(Null)0.0%	(Null)0.0%	(Null)0.0%	(Null)0.0%	(Null)0.0%	(Null)0.0%	(Null)0.0%	(Null)0.0%	(Null)0.0%	(Null)0.0%	(Null)0.0%	(Null)0.0%	(Null)0.0%	(Null)0.0%	(Null)0.0%	(Null)0.0%	(Null)0.0%
Enterprises Count, Total	371	358.8	343.3	330.6	320.6	311.2	306	296.8	292.6	288.6	288.5	288	258.8	247.8	240.1	230.9
SMEs	369.5	357.3	341.9	329.2	319.3	310	304.7	295.5	291.3	287.3	287.2	286.7	257.6	246.6	238.9	229.7
Non-SMEs	1.5	1.4	1.4	1.4	1.3	1.2	1.3	1.3	1.3	1.3	1.3	1.3	1.3	1.2	1.2	1.1
Employment Of Enterprises, Total	3.6	3.55	3.49	3.41	3.16	3.13	3.32	3.25	3.21	3.24	3.25	3.21	3.1	2.96	2.83	2.72
SMEs	2.49	2.46	2.41	2.35	2.18	2.19	2.33	2.3	2.28	2.31	2.31	2.27	2.18	2.09	2.02	1.97
Non-SMEs	1.11	1.09	1.08	1.05	0.98	0.93	0.99	0.95	0.93	0.93	0.94	0.93	0.92	0.87	0.81	0.76
Nominal Value Added Of Enterprises, Total	714.7	695.9	626.3	656.7	543.3	443.5	469.5	465.5	429.8	399	381.1	359.4	345.4	331.9	317.8	297.7
SMEs	327.8	322.7	296.9	295.5	258.1	211.5	209.8	207.7	206.6	196	185.1	184.2	177.3	162.2	159.9	153.6
Non-SMEs	386.9	373.2	329.4	361.2	285.2	232.1	259.6	257.8	223.2	203	196	175.2	168.2	169.7	157.9	144.1
Share Of Enterprises Count, Total	100	100	100	100	100	100	100	100	100	100	100	100	100	100	100	100

Google colab link

Analyse this dataset with Colab Notebook

1. Copy this dataset ID: d_f9c93c1ffcefe660272c101cd733711c
2. Click on the button below

Column legend

Title	Column name	Data type	Unit of measure	Description
Data Series	DataSeries	Text	Thousand	-
2025	2025	Numeric	Thousand	-
2024	2024	Numeric	Thousand	-
2023	2023	Numeric	Thousand	-
2022	2022	Numeric	Thousand	-
2021	2021	Numeric	Thousand	-
2020	2020	Numeric	Thousand	-
2019	2019	Numeric	Thousand	-
2018	2018	Numeric	Thousand	-
2017	2017	Numeric	Thousand	-