• 2018od4a-video
  • water consumption and cost 2012 2016

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 water_consumption_and_cost_2013_2020 table in this repository, by referencing it like:


or in a full query, like:

    ":id", -- Socrata column ID
    "development_name", -- The name of the housing development as listed in the Development Data Book. 
    "water_sewer_charges", -- Total water & sewer charges 
    "service_end_date", -- Bill end date 
    "service_start_date", -- Bill start date 
    "revenue_month", -- Year and month of bill: 2016-01 
    "meter_number", -- Meter number 
    "current_charges", -- Total costs 
    "borough", -- Bronx, Brooklyn, Manhattan, Queens, or Staten Island. 
    "amp", -- Abbreviation for Asset Management Project (AMP) numbers.  HUD Development asset tracking number.  An AMP number can consist of more than one development. 
    "rc_code", -- "NYCHA budget responsibility code.  Code representing a specific development. " 
    "edp", -- NYCHA Electronic Data Processing. Number used to identify individual NYCHA developments. EDP is used by NYCHA only to link data issued from a different system (the energy management system that was used by NYCHA before 2010). It is recommended to use the TDS # as a unique identifier of each development. 
    "bill_analyzed", -- The bill was analyzed for billing errors by NYCHA's Utility Management system during the billing period 
    "rate_class", -- The rate applied to the account.  Details about each rate (dollar value) are available on the vendor web site. 
    "funding_source", -- "The development’s funding source including Federal, Mixed Finance, or an indication that the facility is a non development facility which means a non residential facility." 
    "meter_amr", -- Is the meter Automatic Meter Reading (AMR), Interval or none 
    "consumption_hcf", -- Total HCF (Hundred Cubic Feet) consumption 
    "days", -- Number of days on bill 
    "meter_scope", -- The buildings or areas the account and meter supply 
    "account_name", -- The name of the housing development as listed in the Development Data Boo
    "tds", -- TDS (Tenant Data System) number is the unique identifier for all NCYHA developments. It is recommended to use it in order to run analysis by development. The TDS is also the unique link between NYCHA data sets. 
    "location", -- "Building number.  In order to run an analysis by building, you can use a combination of TDS and building number which gives a unique identifier for each building" 
    "vendor_name", -- Utility vendor name 
    "estimated", -- Meter was not read for the time period. The consumption and cost are estimated. (Data is updated with actual reads once the meter is read) 
    "other_charges" -- Total other charges 
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/water-consumption-and-cost-2013-2020-66be-66yr 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/water-consumption-and-cost-2013-2020-66be-66yr: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/water-consumption-and-cost-2013-2020-66be-66yr" \
  --handler-options '{
    "domain": "",
    "tables": {
        "water_consumption_and_cost_2013_2020": "66be-66yr"

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/water-consumption-and-cost-2013-2020-66be-66yr is just another Postgres schema.

Related Documentation: