The Complete CBS Data Set on Snowflake
Get direct access to all official statistics of the Netherlands. Forget manual downloads or the hassle of complex API links: the complete dataset of Statistics Netherlands is ready for you in your own Snowflake environment.
Whether you are doing deep trend analysis, building market models or filling your dashboards; you now have the power of decades of Dutch data right under the button. Structured, translated and always up to date.
Access on the Snowflake Marketplace
More info on the dataset and instructions can be found in the listing on the Snowflake Marketplace.
What's in it?
You don't just get a subset, but the entire portfolio of the Central Bureau of Statistics. We've prepared thousands of tables for you, divided into three main categories:
Historical Data
Dive into decades-long trends about the labor market and demographics.
Economics & Finance
From national accounts and price indices to detailed trade statistics.
Society & Sustainability
Insights into healthcare, the housing market, energy transition and how the Dutch use ICT.
Automated updates and readable data
Daily synchronization (01:00)
Metadata and readability
CBS Data Warehouse: A 12-Scheme Walkthrough
- LEGACY (Archives & Longitudinal Series) A large collection of historical and
longitudinal datasets, often spanning multiple decades. These include labor market
trends and demographic developments. They follow earlier structural conventions
and are primarily used for long-term trend analysis. - SPECIALIZED (Custom & Non-Standard Datasets) A collection of non-standard
datasets with Alpha-IDs (like gir97 or plaats99) that do not fit the numeric schema
patterns. These contain highly specific indices, experimental surveys, or
custom-structured extracts that require bespoke handling.
- STANDARD_70 (Industry, Prices & Environment) Primarily includes industrial
statistics, price indices, and environmental or agricultural data. These reflect early
standardization efforts and follow consistent structures with older metadata
conventions. - STANDARD_71 (Finance & Macro-Economic Statistics) A diverse collection of
financial datasets, including institutional accounts, exchange rates, and broader
economic indicators aligned with established statistical frameworks. - STANDARD_72_74 (Cross-Domain Statistical Frameworks) A set of datasets
providing structural or cross domain statistical outputs, often used as supporting
frameworks or reference tables within the broader CBS ecosystem. - STANDARD_75_79 (Energy, Business Dynamics & Legal Indicators) Focuses on
renewable energy production, enterprise demographics, and legal-economic
outcomes like corporate insolvencies. This is the core bucket for industrial energy
and business health
- MODERN_80_81 (Core Economic & Statistical Outputs) The largest collection of
modern datasets, including national accounts, trade statistics, and key economic
indicators that form the backbone of modern analytical workflows. - MODERN_82 (Socio-Economic & Household Statistics) Primarily includes
datasets on households, income, and socio economic conditions, such as poverty
measures and income distribution for population-level analysis. - MODERN_83 (Population, Health & Social Data) Focuses on demographic
developments, health statistics, and social outcomes, including large survey-based
datasets like national health monitors. - MODERN_84 (Sustainability, ICT & Environmental Indicators) Contains a
concentration of datasets related to ICT usage in businesses and modern
sustainability metrics. This bucket represents the modern digital and environmental
reporting standards. - MODERN_85 (Labor Market & Structural Change) Includes datasets on
employment, labor participation, and structural economic developments, capturing
the most recent shifts in the labor market. - MODERN_86_99 (Recent & Evolving Datasets) A forward looking collection of the
most recently added datasets. These follow the latest schema conventions and
reflect ongoing updates in statistical production.
The Logic Behind Our Taxonomy
We didn’t just dump 6,000 tables into Snowflake. To keep the data actionable and intuitive, we decoded the CBS ID taxonomy to create a continuous timeline rather than a collection of scattered fragments.
How does this work in practice? For example, if a table started in 1985 but CBS added new data for 2026 to it last week, we keep that dataset in the LEGACY schemas. This ensures that a 40-year trend line remains fully intact and organized in one place, instead of being broken into separate pieces across different schemas.
However, if you are looking for the most current, specifically modern indicators—such as this morning’s Inflation Index or the latest Energy Transition data—you can head straight to schemas like MODERN_84. This approach ensures you are always working with the most reliable and logical source for your specific analysis.
Access on the Snowflake Marketplace
More info on the dataset and instructions can be found in the listing on the Snowflake Marketplace.