• budget
  • capital
  • cip
  • expenditures
  • expenses
  • + 1

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 cip_budget table in this repository, by referencing it like:


or in a full query, like:

    ":id", -- Socrata column ID
    "project_actuals", -- The current accumulated expenditures for a specific project.
    "major_program_name", -- A project the City is working on. Generally, a major program is created to capture all of the costs of creating a new or improving an existing asset before the asset is placed in service. Major programs may also track costs related to a grant awarded to the City.
    "major_program", -- The number assigned to a project.
    "fund", -- The governmental segment that benefited from the transaction. For the capital dataset, we have set a default name for this as Capital Project Funding as funds are not loaded in Budget Structure 37.
    "project_budget", -- The current project budget for the total project cost over the life of the project.
    "project_phase_name", -- A project is split into phases which generally represent Pre-design/Design/Construction or may be split into Purchases (where no construction is involved in the acquisition of the asset).
    "project_phase", -- The number assigned to a phase of a project.
    "program", -- The number assigned to a program.
    "major_program_category_name", -- The lowest level of classification of City projects.  The projects assigned to each major program class are further separated into smaller groupings.  Similar to the major program class, all City projects are only assigned to one of these classifications.
    "major_program_class", -- The number assigned to the major program classification.
    "program_name", -- A program represents a smaller segment of a project the City is working on. For example, the project is installing a full irrigation system and each program will represent each park included in the project.
    "major_program_category", -- The number assigned to the major program category.
    "major_program_class_name", -- The highest level of classification of City projects.  There are currently five different classifications; General Government, Parks & Culture, Public Safety, Transportation, and Utilities. All projects are assigned to one of these classifications.
    "fiscal_year" -- A 12-month period of time to which the Annual Budget applies and at the end of which, a governmental unit determines its financial position and the results of its operations.  For the City of Mesa, the fiscal year is July 1 through June 30.
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 citydata-mesaaz-gov/cip-budget-9bk7-3e9s with SQL in under 60 seconds.

This repository is an "external" repository. That means it's hosted elsewhere, in this case at When you querycitydata-mesaaz-gov/cip-budget-9bk7-3e9s: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 \
  "citydata-mesaaz-gov/cip-budget-9bk7-3e9s" \
  --handler-options '{
    "domain": "",
    "tables": {
        "cip_budget": "9bk7-3e9s"

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, citydata-mesaaz-gov/cip-budget-9bk7-3e9s is just another Postgres schema.

Related Documentation: