Queria

Open data you can aggregate directly — no ETL, no prep work

Queria is a data catalogue that publishes its data as a database. No download, no conversion — connect straight from the browser, Python, your BI tool or an AI agent. You never hold a copy, so what you query is always current.

No sign-in required. Query it as it is, and export to CSV, Parquet or Excel whenever you need a copy.

Across every publisher

You don't have to know who published it

Usually the only clues you get are a file name and a description. Queria searches across publishers at the table and the column level. Every hit carries its type, and where the publisher documented a meaning that shows too — so you can tell whether it fits before you open it.

人口
TablesColumnsDatasetsSchemas
人口総数population_totalINTEGER日本人と外国人の合計(人)queria/metro_tokyo›stats.resident_population
2025年推計人口population_2025DOUBLE人queria/nlftp›population.future_population_municipality
該当性別・年齢層の人口populationBIGINTqueria/tsukuba›main.mart_tsukuba_population

A column search for 人口 (population) — Tokyo, the national land ministry and the city of Tsukuba in one result

Try a column search

Ready to use

The prep work is already done

We align encodings, column names and units, fill in coordinates from the address when a facility has none, absorb gaps and inconsistencies, and ship the meaning and unit of every column with the data. Nobody has to write that same preprocessing again.

A table written for peopleWindows-1252 / CSV, with broken values
XX City Evacuation Sites (as of April 2026)
* Updated every April. Contact the division about the Notes column.
ID,Facility,,Address,Notes
,,Short name,,
1.30E+09,XX Elementary School,XX ELEM,120 Main Street,Gymnasium
1.30E+09,XX Middle School,,45 Oak Ave.,-
1.30E+09,XX Community Center,,-,-
A table machines can read tooUTF-8 / Parquet, breakage repaired
idfacility IDnamefacility nameaddressstreet addresslatlatitudelonlongitude
1301000012XX Elementary School120 Main St40.7128-74.0060
1301000013XX Middle School45 Oak Ave40.7061-73.9969
1301000014XX Community CenterNULLNULLNULL

Combine them

Data from separate publishers becomes one table

Two publishers can describe the same municipality with different column names and a different number of digits in the code. Queria aligns that as the data is loaded, so data published separately lines up as it is.

国土交通省将来推計人口(1 市区町村 1 行)
市区町村コード
27216
高齢化率(2050)
52.6%
厚生労働省介護事業所(1 事業所 1 行)
市区町村コード
27216
サービスの種類
訪問介護

matched on the same municipality code, then counted

The combined result
市区町村
大阪府 河内長野市
高齢化率(2050)
52.6%
訪問介護の事業所数
48

Population projections from the land ministry matched against care-service providers from the health ministry, on the municipality code. Every value is taken from data published on Queria today.

Read analyses that span publishers

Your own tools

No ETL, from anywhere

Everything is published as a database rather than as files, so there is nothing to convert and nothing to load. The same data, the same SQL, wherever you work.

BrowserSQL the moment you open a table. No install, no sign-in.
PythonConnect with the queria package and read into a DataFrame.
BI toolsTableau and anything else that speaks DuckDB.
AI agentsStraight from Claude Code over the MCP server.
One command. Nothing to install, nothing to ATTACH
uvx queria sql "SELECT * FROM calendar.main.mart_calendar LIMIT 10"
Export in whatever format you need:CSVJSONParquetExcelGoogle Sheets

Each dataset refreshes on its own published schedule. The connection never changes, so the next time you open it you are already on the new data. Every dataset card shows when it was last updated, and the refresh schedule wherever the publisher declared one.

See how to connect

For publishers

What you publish gets used as it is

The preprocessing every user used to write on their own gets done once, on the publishing side. That is what publishing on Queria means: the job does not end at publication — what happens next changes.

Usable the moment it lands

Column names and units arrive aligned, so people can use the data without downloading or reshaping it.

Alongside other publishers

Municipality codes and coordinates line up, so datasets published separately can be joined together.

You can see it being used

We measure how much your data is used and report it back, so you can judge what publishing is worth.

Talk to us about publishing

Open to everyone, right now

Working with open data is free for individuals, and the source is public. Even without signing in, you can look inside a dataset and aggregate it right there.

The aggregation runs in DuckDB on your side. There is no query server on ours, so wider use does not raise what it costs us to run — which is why we can keep it open and free.