QuickBooks to Postgres

This page provides you with instructions on how to extract data from QuickBooks and load it into PostgreSQL. (If this manual process sounds onerous, check out Stitch, which can do all the heavy lifting for you in just a few clicks.)

What is QuickBooks?

QuickBooks is Intuit's accounting software, which is available in both Desktop and Online editions. Targeted at small and medium-sized businesses, it manages payroll, inventory, and sales, and includes marketing tools, merchant services, and training resources.

What is PostgreSQL?

PostgreSQL, known by most simply as Postgres, is a hugely popular object-relational database management system (ORDBMS). It labels itself as "the world's most advanced open source database," and for good reason. The platform, despite being available for free via an open source license, offers enterprise-grade features including a strong emphasis on extensibility and standards compliance.

It runs on all major operating systems, including Linux, Unix, and Windows. It is fully ACID-compliant, has full support for foreign keys, joins, views, triggers, and stored procedures (in multiple languages). Postgres is often the best tool for the job as a back-end database for web systems and software tools, and cloud-based deployments are offered by most major cloud vendors. Its syntax also forms the basis for querying Amazon Redshift, which makes migration between the two systems relatively painless and makes Postgres a good "first step" for developers who may later expand into Redshift's data warehouse platform.

Getting data out of QuickBooks

To load QuickBooks data to a data warehouse, first pull the data off of QuickBooks' servers using the QuickBooks Accounting and Payments APIs, which are discussed in the QuickBooks programming guide.

Sample QuickBooks data

QuickBooks' APIs return XML-formatted data, as in this example.

<IntuitResponse xmlns="http://schema.intuit.com/finance/v3" time="2017-04-03T10:22:55.766Z">
 <QueryResponse startPosition="10" maxResults="2">
 <Customer>
 <Id>2123</Id>
 <SyncToken>0</SyncToken>
 ...
 <GivenName>Srini</GivenName>
 </Customer>
 <Customer>
 <Id>2124</Id>
 <SyncToken>0</SyncToken>
 ...
 <GivenName>Peter</GivenName>
 </Customer>
 </QueryResponse>
</IntuitResponse>

Loading data into Postgres

Once you have identified all of the columns you will want to insert, you can use the CREATE TABLE statement in Postgres to create a table that can receive all of this data. Then, Postgres offers a number of methods for loading in data, and the best method varies depending on the quantity of data you have and the regularity with which you plan to load it.

For simple, day-to-day data insertion, running INSERT queries against the database directly are the standard SQL method for getting data added. Documentation on INSERT queries and their bretheren can be found in the Postgres documentation here.

For bulk insertions of data, which you will likely want to conduct if you have a high volume of data to load, other tools exist as well. This is where the COPY command becomes quite useful, as it allows you to load large sets of data into Postgres without needing to run a series of INSERT statements. Documentation can be found here.

The Postgres documentation also provides a helpful overall guide for conducting fast data inserts, populating your database, and avoiding common pitfalls in the process. You can find it here.

Keeping QuickBooks data up to date

It's great that you've developed a script that pulls data from QuickBooks and loads it into a data warehouse, but what happens when you have new transactions, invoices, and payments?

The key is to build your script in such a way that it can identify incremental updates to your data. Use fields like CreateTime and LastUpdatedTime to identify records that are new since your last update, or since the most recent record you copied. Once you've taken new data into account, you can set up your script as a cron job or continuous loop to keep pulling down new data as it appears.

Other data warehouse options

PostgreSQL is great, but sometimes you need to optimize for different things when you're choosing a data warehouse. Some folks choose to go with Amazon Redshift, Google BigQuery, or Snowflake, which are RDBMSes that use similar SQL syntax, or Panoply, which works with Redshift instances. If you're interested in seeing the relevant steps for loading data into one of these platforms, check out To Redshift, To BigQuery, To Snowflake, and To Panoply.

Easier and faster alternatives

If all this sounds a bit overwhelming, don’t be alarmed. If you have all the skills necessary to go through this process, chances are building and maintaining a script like this isn’t a very high-leverage use of your time.

Thankfully, products like Stitch were built to solve this problem automatically. With just a few clicks, Stitch starts extracting your QuickBooks data via the API, structuring it in a way that is optimized for analysis, and inserting that data into your PostgreSQL data warehouse.