Icon for Socrata external plugin

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 nypd_complaint_data_current_year_to_date table in this repository, by referencing it like:


or in a full query, like:

    ":id", -- Socrata column ID
    "crm_atpt_cptd_cd", -- Indicator of whether crime was successfully completed or attempted, but failed or was interrupted prematurely
    "housing_psa", -- Development Level Code
    "hadevelopt", -- Name of NYCHA housing development of occurrence, if applicable
    "cmplnt_to_tm", -- Ending time of occurrence for the reported event, if exact time of occurrence is unknown
    "pd_cd", -- Three digit internal classification code (more granular than Key Code)
    "law_cat_cd", -- Level of offense: felony, misdemeanor, violation 
    "boro_nm", -- The name of the borough in which the incident occurred
    "vic_sex", -- Victim’s Sex Description
    "parks_nm", -- Name of NYC park, playground or greenspace of occurrence, if applicable (state parks are not included)
    "patrol_boro", -- The name of the patrol borough in which the incident occurred
    "x_coord_cd", -- X-coordinate for New York State Plane Coordinate System, Long Island Zone, NAD 83, units feet (FIPS 3104)
    "transit_district", -- Transit district in which the offense occurred. 
    "station_name", -- Transit station name
    "rpt_dt", -- Date event was reported to police 
    "y_coord_cd", -- Y-coordinate for New York State Plane Coordinate System, Long Island Zone, NAD 83, units feet (FIPS 3104)
    "latitude", -- Midblock Latitude coordinate for Global Coordinate System, WGS 1984, decimal degrees (EPSG 4326) 
    "longitude", -- Midblock Longitude coordinate for Global Coordinate System, WGS 1984, decimal degrees (EPSG 4326)
    "ofns_desc", -- Description of offense corresponding with key code
    "jurisdiction_code", -- Jurisdiction responsible for incident. Either internal, like Police(0), Transit(1), and Housing(2); or external(3), like Correction, Port Authority, etc.
    "juris_desc", -- Description of the jurisdiction code
    "loc_of_occur_desc", -- Specific location of occurrence in or around the premises; inside, opposite of, front of, rear of
    "ky_cd", -- Three digit offense classification code
    "prem_typ_desc", -- Specific description of premises; grocery store, residence, street, etc.
    "pd_desc", -- Description of internal classification corresponding with PD code (more granular than Offense Description)
    "cmplnt_to_dt", -- Ending date of occurrence for the reported event, if exact time of occurrence is unknown
    "cmplnt_fr_tm", -- Exact time of occurrence for the reported event (or starting time of occurrence, if CMPLNT_TO_TM exists)
    "cmplnt_fr_dt", -- Exact date of occurrence for the reported event (or starting date of occurrence, if CMPLNT_TO_DT exists)
    "addr_pct_cd", -- The precinct in which the incident occurred
    "cmplnt_num", -- Randomly generated persistent ID for each complaint 
    "vic_race", -- Victim’s Race Description
    "vic_age_group", -- Victim’s Age Group
    "susp_sex", -- Suspect’s Sex Description 
    "susp_race", -- Suspect’s Race Description
    "susp_age_group" -- Suspect’s Age Group
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 cityofnewyork-us/nypd-complaint-data-current-year-to-date-5uac-w243 with SQL in under 60 seconds.

This repository is an "external" repository. That means it's hosted elsewhere, in this case at When you querycityofnewyork-us/nypd-complaint-data-current-year-to-date-5uac-w243: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 \
  "cityofnewyork-us/nypd-complaint-data-current-year-to-date-5uac-w243" \
  --handler-options '{
    "domain": "",
    "tables": {
        "nypd_complaint_data_current_year_to_date": "5uac-w243"

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, cityofnewyork-us/nypd-complaint-data-current-year-to-date-5uac-w243 is just another Postgres schema.

Related Documentation: