Query the Data Delivery Network

Query the DDN

The 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 procotol. Any Splitgraph user can connect to it at and query any version of over 40,000 datasets that are hosted or proxied by Splitgraph.

For example, you can query the bird_distribution_and_abundance_ocean_survival_of table in this repository, by referencing it like:


or in a full query, like:

    ":id", -- Socrata column ID
    "decimal_latitude", -- This is the latitude of the survey station.
    "local_month", -- This is the local month, represented as text.
    "month", -- This is the calendar month, represented as a number.
    "station_code", -- This is the unique database code used to identify an oceanographic station for a given year, month, and day.
    "transect_name", -- This is the two-letter designation for each east-west survey transect in the survey.
    "station_name", -- This is the nearest survey station to which a given bird (or other) density has been assigned.
    "segment_species_count", -- This is the total count, in whole numbers, of species sightings assigned to a given station.
    "distance_from_shore", -- This is the distance (in nautical miles) of the survey station from the shoreline where the transect line would intersect the coastline if it were extended all the way to shore.
    "year", -- This is the calendar year; add "2000" to get the year, e.g. "3" = "2003", "11" = "2011".
    "species_code", -- These are four-letter species codes that typically follow the American Ornithologists' Union code for bird species or taxon (see For marine mammals, large fishes, or other objects, a similar four-letter code is assigned to that sighting.
    "log_density", -- This is the logarithm, base 10, of the raw density.
    "segment_distance_for_sums", -- This is the segment distance (in kilometers) along the transect that was assigned to a given station.
    "area_surveyed_for_sums", -- This is the area covered by the visual survey (in square kilometers) and over which species sightings were summed and assigned to a given station.
    "density", -- This is the density, in individuals per square kilometer, assigned to a given survey station.
    "local_date", -- This is the local date represented in DD-MM-YY format, where YY begins from the year 2000.
    "decimal_longitude" -- This is the longitude of the survey station.
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 noaa-fisheries-nwfsc-data-socrata/bird-distribution-and-abundance-ocean-survival-of-c4sv-jh2f with SQL in under 60 seconds.

This repository is an "external" repository. That means it's hosted elsewhere, in this case at When you querynoaa-fisheries-nwfsc-data-socrata/bird-distribution-and-abundance-ocean-survival-of-c4sv-jh2f:latest on the DDN, we "mount" the repository using the socrata mount handler. The mount handler proxies your SQL query to the upstream data source, translating it from SQL to the relevant language (in this case SoQL).

We also cache query responses on the DDN, but we run the DDN on multiple nodes so a CACHE_HIT is only guaranteed for subsequent queries that land on the same node.

Query Your Local Engine

Install Splitgraph Locally
bash -c "$(curl -sL"

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 (like this repository), 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, where the author has pushed Splitgraph Images to the repository, you can "clone" and/or "checkout" the data using sgr cloneand sgr checkout.

Mounting Data

This repository is an external repository. It's not hosted by Splitgraph. It is hosted by, and Splitgraph indexes it. This means it is not an actual Splitgraph image, so you cannot use sgr clone to get the data. Instead, you can use the socrata adapter with the sgr mount command. Then, if you want, you can import the data and turn it into a Splitgraph image that others can clone.

First, install Splitgraph if you haven't already.

Mount the table with sgr mount

sgr mount socrata \
  "noaa-fisheries-nwfsc-data-socrata/bird-distribution-and-abundance-ocean-survival-of-c4sv-jh2f" \
  --handler-options '{
    "domain": "",
    "tables": {
        "bird_distribution_and_abundance_ocean_survival_of": "c4sv-jh2f"

That's it! Now you can query the data in the mounted table like any other Postgres table.

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, noaa-fisheries-nwfsc-data-socrata/bird-distribution-and-abundance-ocean-survival-of-c4sv-jh2f is just another Postgres schema.

Related Documentation: