• checks
  • invoices
  • purchase order
  • spending
  • suppliers
  • + 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 county_spending table in this repository, by referencing it like:


or in a full query, like:

    ":id", -- Socrata column ID
    "payment_id", -- The identifying number on the paper check, electronic payment, or credit card transactions. 
    "payment_method", -- Type of payment, such as check, EFT, credit card (MCG JPM SUA) or wire transactions. 
    "inv_date", -- "The Invoice date is the date listed in ERP as the invoice date and may contain a null value.    " 
    "invoice_id", -- A number assigned to an invoice, used to uniquely identify a supplier’s invoice. 
    "po_line", -- The line number for a specific item or service that is being purchased on the Purchase Order (PO). (For example, if five different items are purchased, then there will be five PO lines.) 
    "contract_num", -- A unique number used to identify a County contract. 
    "vendor", -- Supplier name  
    "fund", -- Accounting device that the County uses to keep track of specific sources of funding and spending for particular purposes   (Example: General Fund, Grant Fund; CIP Fund) 
    "program", -- Subdivision of Departments made up of a primary service, function, or set of activities which address a specific responsibility or goal within an agency's mission.  (Example:   Operations, Budget, Aquatics).  
    "fiscal_year_period", -- Our fiscal year runs July 1st through June 30th.  A period is equal to one month (Example:   period 1 is July, period 2 is August, period 3 is September, etc.) 
    "vendor_zip", -- The zip code for the supplier’s address to which the supplier’s payment is sent. 
    "vendor_id", -- A unique supplier identification number 
    "description", -- Lowest level of description regarding how the County expends monies (Example:   local travel). 
    "account_code", -- A unique account identification number (related to Account Name field)  
    "payment_status", -- Status of a payment through the banking system, such as Negotiable, Void, or Reconciled. 
    "category", -- Represents how data is presented on the County’s financial statements (expense, revenue, liability, asset, owner’s equity or fund balance). 
    "service", -- High Organization level grouping, such as Public Safety and Community Development. 
    "invoice_line", -- A line number from a supplier invoice, for the County’s purchase of a good or a service. 
    "expense_category", -- The highest level grouping of account codes that the County has spent funds on.  For example, the “Travel” expense. 
    "department", -- The name of the Department. 
    "fiscal_year", -- The County’s fiscal year (such as 2015) represents a 12 month period used for annual financial reporting beginning July 1st through June 30th. 
    "po_num", -- A unique number used to identify a purchase order issued to a vendor. 
    "payment_date", -- The date the check was written or the payment was made. 
    "amount", -- The dollar amount associated with an invoice distribution line. 
    "invoice_distribution_line" -- The line number indicating which Department(s) or Program(s) the  invoice is charged to.  (For example, if five different departments are being charged for an item, then there will be five distribution lines.) 
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 montgomerycountymd-gov/county-spending-vpf9-6irq with SQL in under 60 seconds.

This repository is an "external" repository. That means it's hosted elsewhere, in this case at When you querymontgomerycountymd-gov/county-spending-vpf9-6irq: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 \
  "montgomerycountymd-gov/county-spending-vpf9-6irq" \
  --handler-options '{
    "domain": "",
    "tables": {
        "county_spending": "vpf9-6irq"

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, montgomerycountymd-gov/county-spending-vpf9-6irq is just another Postgres schema.

Related Documentation: