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 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 animal_inventory_fiscal_year_2020_2021 table in this repository, by referencing it like:


or in a full query, like:

    ":id", -- Socrata column ID
    "animal_origin", -- Notates whether the animal came in through DAS' Pet Support Lobby (Over the Counter) or through Field Services (Field).
    "impound_number", -- Unique number assigned to each impound performed by DAS staff; each impound can include multiple animals.
    "receipt_number", -- Unique number assigned to a financial transaction in the database. 
    "outcome_type", -- Final outcome of the animal if they are no longer under the care of DAS at the time of the report.
    "due_out", -- Date the animal's stray hold expires and animal will be available for non-return to owner outcomes; date DAS has full ownership of the animal based on city ordinance.
    "intake_date", -- Date the animal was intaken by DAS.
    "intake_subtype", -- Additional categorization of purpose of intake; used primarily to analyze intake trends.
    "census_tract", -- Unique area mapped out by the federal government for purposes of the census.
    "source_id", -- Person who initiated the intake.
    "activity_number", -- Unique number assigned to an activity related to a service request.
    "kennel_number", -- Location of the animal at the time of the report
    "animal_breed", -- Breed of the animal; typically a visual breed estimation.
    "animal_stay_days", -- Number of days an animal has been in the care of DAS.
    "additional_information", -- Additional staff notes.
    "intake_condition", -- Apparent medical condition of the animal when it was taken in by DAS.
    "staff_id", -- Unique ID number assigned to the staff person who entered the record.
    "reason", -- Reason that an animal was surrendered to or brought to DAS.
    "animal_id", -- Unique number assigned to each animal when their record is created in the database. 
    "outcome_condition", -- Apparent medical condition of the animal when it was released from DAS.
    "animal_type", -- Animal category: dog, cat, wildlife, other, etc. 
    "chip_status", -- Notates whether staff were successful in scanning animal for a microchip.
    "outcome_time", -- Time the animal was outcomed by DAS / left DAS' care.
    "intake_type", -- Type or purpose of intake; used primarily to analyze intake trends.
    "outcome_date", -- Date the animal was outcomed by DAS / left DAS' care.
    "kennel_status", -- Availability of the animal. 
    "service_request_number", -- Unique number assigned to a service request by Salesforce when it is submitted by a resident through 3-1-1.
    "month", -- Month the record was created.
    "council_district", -- Unique area mapped out by the City of Dallas that is represented by a specific City Council Office and Member.
    "activity_sequence", -- Sequence starts with 1 usually then a follow up sequence is created until activity is completed.
    "year", -- City of Dallas Fiscal Year the record was created.
    "hold_request", -- Routing or pathway identified for the animal at the time of the report. Pathways are used to move animals towards the outcome management recommends at the time based on behavior, medical condition, and history. Pathways are reviewed and updated frequently as an animal's behavior or medical condition changes.
    "intake_time" -- Time the animal was intaken by DAS.
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 dallasopendata/animal-inventory-fiscal-year-2020-2021-r24h-29gi with SQL in under 60 seconds.

This repository is an "external" repository. That means it's hosted elsewhere, in this case at www.dallasopendata.com. When you querydallasopendata/animal-inventory-fiscal-year-2020-2021-r24h-29gi: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 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 (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 www.dallasopendata.com, 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 \
  "dallasopendata/animal-inventory-fiscal-year-2020-2021-r24h-29gi" \
  --handler-options '{
    "domain": "www.dallasopendata.com",
    "tables": {
        "animal_inventory_fiscal_year_2020_2021": "r24h-29gi"

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, dallasopendata/animal-inventory-fiscal-year-2020-2021-r24h-29gi is just another Postgres schema.