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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 protocol. 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 highway_quality_in_colorado_2014 table in this repository, by referencing it like:


or in a full query, like:

    ":id", -- Socrata column ID
    "hwy", -- A Unique (3 Number - 1 Letter) Highway Identification Code or Designating for a State Highway, Business Route, U.S. Route or Tolled Facility. Odd numbers typically run North and South and Even numbers typically Run East and West.
    "dir", -- Traffic flow direction
    "bmp", -- Beginning milepoint
    "emp", -- Ending milepoint
    "length", -- Length of highway segment (in miles)
    "region", -- A Domained Value Element (Region: 1-6) used to identify the Engineering Region number in which the Road Segment is located.
    "year", -- Year finished
    "funcl", -- Indicates the functional category and usage limitations of the segment of road, as defined by FHWA, and is broken down between rural and urban areas.
    "county", -- Name of the county the road segment lies in
    "ptyp", -- Pavement Type Classifications: 1 - Asphalt, 2 - Asphalt over concrete, 3 - Concrete, 4 - Concrete over asphalt
    "trafz", -- Traffic Classifications: 1 - Low (<0.3 million design equivalent single access load [ESAL]), 2 - Medium (0.3 - 3 million ESAL), 3 - High (3 - 10 million ESAL), 4 - Very High (10 - 30 million ESAL), 5 - Very Very High (> 30 million ESAL)
    "envz", -- Climate Classifications: 1 - Very cool (< 81 degrees), 2 - Cool (81 - 88), 3 - Moderate (88 - 97), 4 - Hot (>97)
    "depth", -- Thickness Classifications: 1 - Asphalt <4" thick or Concrete <8" thick, 2 - Asphalt <6" thick or Concrete >=8" thick, 3 - Asphalt >= 6" thick
    "numlanes", -- Number of lanes in the road segment
    "pgrp", -- Pavement group, which is a combination of the pavement, traffic, and climate classifications. 1323 means Asphalt, High Traffic, Cool Environment, >= 6" Thick
    "nhs", -- A Domained Value Element (NHSDesig: 0-9) used to identify whether the Road Segment is designated as being part of the National Highway System. Also contains the text value (added at the end)
    "iri", -- International roughness index (IRI) correlates somewhat with human exposure to whole-body vibration in vehicles and thus to perceived ride quality reading for the surface condition in the Primary Direction of Travel. Scaled to a score of 1-100.
    "rut", -- A value between 0 and 100 that is used to calculate Remaining Service Life for rutting. A value of 100 indicates .15 inch or less rutting. A value of 50 is the threshold that indicates no more remaining service life. This occurs at an average rut depth of .55 inches.
    "fatg", -- The amount of fatigue normalized on a scale of 0-100 (where 0 is the worst pavement in existence and 100 is a perfect pavement)
    "tran", -- The amount of transverse cracking normalized on a scale of 0-100 (where 0 is the worst pavement in existence and 100 is a perfect pavement)
    "long", -- The amount of logitudinal cracking normalized on a scale of 0-100 (where 0 is the worst pavement in existence and 100 is a perfect pavement)
    "crbk", -- The amount of corner breaks normalized on a scale of 0-100 (where 0 is the worst pavement in existence and 100 is a perfect pavement)
    "dl", -- The drivability life, which is the number of years a pavement has left until it is no longer an acceptable driving surface
    "dlidx", -- For CDOT internal use
    "curve", -- For CDOT internal use
    "mtcy", -- For CDOT internal use
    "mtcd", -- For CDOT internal use
    "cond" -- Condition of the road: LOW, MODERATE, HIGH
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 colorado-gov/highway-quality-in-colorado-2014-49ck-u67r with SQL in under 60 seconds.

This repository is an "external" repository. That means it's hosted elsewhere, in this case at When you querycolorado-gov/highway-quality-in-colorado-2014-49ck-u67r: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 \
  "colorado-gov/highway-quality-in-colorado-2014-49ck-u67r" \
  --handler-options '{
    "domain": "",
    "tables": {
        "highway_quality_in_colorado_2014": "49ck-u67r"

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, colorado-gov/highway-quality-in-colorado-2014-49ck-u67r is just another Postgres schema.

Related Documentation: