Query the Data Delivery Network
Query the DDNThe easiest way to query any data on Splitgraph is via the "Data Delivery Network" (DDN). The DDN is a single endpoint that speaks the PostgreSQL wire protocol. Any Splitgraph user can connect to it at data.splitgraph.com:5432 and query any version of over 40,000 datasets that are hosted or proxied by Splitgraph.
For example, you can query the fresh_pond_reservation_usership table in this repository, by referencing it like:
"cambridgema-gov/fresh-pond-reservation-usership-6xy8-cstb:latest"."fresh_pond_reservation_usership"or in a full query, like:
SELECT
":id", -- Socrata column ID
"bpmulti_bike", -- Total cyclist count per hour at the Fresh Pond Bike Path multi sensor. This sensor was decommissioned in 2024.
"weekdaytype", -- weekday or weekend
"fp_avg_hrly_use", -- Average hourly counts on the Perimeter road trail. Used to calculate FPR usership in the annual census report. See the attached Sensor Location and Metadata Appendix for more details.
"year", -- Calendar year
"wtpmulti_bike", -- Total cyclist count per hour at the Water Treatment Plant on the Perimeter Road
"wtpmulti_ped", -- Total pedestrian count per hour at the Water Treatment Plant multi sensor on the Perimeter Road
"wtpmulti", -- Total count per hour (ped and bike) at the Water Treatment Plant multi sensor on the Perimeter Road. Counts were removed during hours with missing pedestrian (WTPMULTI Ped) or bike (WTPMULTI Bike) counts.
"pro_shop", -- Total count per hour at the Pro Shop entrance sensor
"lus", -- Total count per hour at the Lusitania entrance sensor
"lfp", -- Total count per hour at the Little Fresh Pond Perimeter Road sensor
"cg", -- Total count per hour at the Community Garden entrance sensor
"bpmulti_ped", -- Total pedestrian count per hour at the Fresh Pond Bike Path multi sensor. This sensor was decomissioned in 2024.
"datetime", -- DateTime of the counter result in Eastern time. The hour is the beginning of the hour-long time period recorded in each row. See the attached Sensor Location and Metadata Appendix for more information.
"bpmulti", -- Total count per hour (ped and bikes) at the Fresh Pond Bike Path multi sensor. This sensor was decomissioned in 2024. Counts were removed during hours with missing pedestrian (BPMULTI Ped) or bike (BPMULTI Bike) counts.
"bn", -- Total count per hour at the Black's Nook entrance sensor
"hourlabels", -- text field of the hour in 12-hour time
"hour", -- 24-hour clock time of the first minute of the hour-long time bin
"weekday", -- weekday name
"day", -- numeric weekday
"month", -- 3-letter month abbreviation
"month_value", -- numeric month
"season", -- The meteorological season of the counter result date
"date", -- The date of the counter result.
"yrdaysleap" -- Number of days in the year (365 for regular, 366 for leap year)
FROM
"cambridgema-gov/fresh-pond-reservation-usership-6xy8-cstb:latest"."fresh_pond_reservation_usership"
LIMIT 100;Connecting to the DDN is easy. All you need is an existing SQL client that can connect to Postgres. As long as you have a SQL client ready, you'll be able to query cambridgema-gov/fresh-pond-reservation-usership-6xy8-cstb with SQL in under 60 seconds.
Query Your Local Engine
bash -c "$(curl -sL https://github.com/splitgraph/splitgraph/releases/latest/download/install.sh)"Read the installation docs.
Splitgraph Cloud is built around Splitgraph Core (GitHub), which includes a local Splitgraph Engine packaged as a Docker image. Splitgraph Cloud is basically a scaled-up version of that local Engine. When you query the Data Delivery Network or the REST API, we mount the relevant datasets in an Engine on our servers and execute your query on it.
It's possible to run this engine locally. You'll need a Mac, Windows or Linux system to install sgr, and a Docker installation to run the engine. You don't need to know how to actually use Docker; sgrcan manage the image, container and volume for you.
There are a few ways to ingest data into the local engine.
For external repositories, the Splitgraph Engine can "mount" upstream data sources by using sgr mount. This feature is built around Postgres Foreign Data Wrappers (FDW). You can write custom "mount handlers" for any upstream data source. For an example, we blogged about making a custom mount handler for HackerNews stories.
For hosted datasets (like this repository), where the author has pushed Splitgraph Images to the repository, you can "clone" and/or "checkout" the data using sgr cloneand sgr checkout.
Cloning Data
Because cambridgema-gov/fresh-pond-reservation-usership-6xy8-cstb:latest is a Splitgraph Image, you can clone the data from Spltgraph Cloud to your local engine, where you can query it like any other Postgres database, using any of your existing tools.
First, install Splitgraph if you haven't already.
Clone the metadata with sgr clone
This will be quick, and does not download the actual data.
sgr clone cambridgema-gov/fresh-pond-reservation-usership-6xy8-cstbCheckout the data
Once you've cloned the data, you need to "checkout" the tag that you want. For example, to checkout the latest tag:
sgr checkout cambridgema-gov/fresh-pond-reservation-usership-6xy8-cstb:latestThis will download all the objects for the latest tag of cambridgema-gov/fresh-pond-reservation-usership-6xy8-cstb and load them into the Splitgraph Engine. Depending on your connection speed and the size of the data, you will need to wait for the checkout to complete. Once it's complete, you will be able to query the data like you would any other Postgres database.
Alternatively, use "layered checkout" to avoid downloading all the data
The data in cambridgema-gov/fresh-pond-reservation-usership-6xy8-cstb:latest is 0 bytes. If this is too big to download all at once, or perhaps you only need to query a subset of it, you can use a layered checkout.:
sgr checkout --layered cambridgema-gov/fresh-pond-reservation-usership-6xy8-cstb:latestThis will not download all the data, but it will create a schema comprised of foreign tables, that you can query as you would any other data. Splitgraph will lazily download the required objects as you query the data. In some cases, this might be faster or more efficient than a regular checkout.
Read the layered querying documentation to learn about when and why you might want to use layered queries.
Query the data with your existing tools
Once you've loaded the data into your local Splitgraph Engine, you can query it with any of your existing tools. As far as they're concerned, cambridgema-gov/fresh-pond-reservation-usership-6xy8-cstb is just another Postgres schema.