Hubstaff Data Integration with Redshift

With Portable, integrate Hubstaff data with your Redshift warehouse in minutes. Access your time tracker data from Redshift without having to manage cumbersome ETL scripts.

The Two Paths to Connect Hubstaff to Amazon Redshift

There are two ways to sync data from Hubstaff into your data warehouse for analytics.

Method 1: Manually Developing a Custom Data Pipeline Yourself

Write code from scratch or use an open-source framework to build an integration between Hubstaff and Redshift.

Method 2: Automating the ETL Process with a No-Code Solution

Leverage a pre-built connector from a cloud-hosted solution like Portable.

How to Create Value with Hubstaff Data

Teams connect Hubstaff to their data warehouse to build dashboards and generate value for their business. Let’s dig into the capabilities Hubstaff exposes via their API, outline insights you can build with the data, and summarize the most common analytics environments that teams are using to process their Hubstaff data.

Extract: What Data Can You Extract from the Hubstaff API?

Hubstaff is a time tracker used for managing the time spent on tasks, productivity and gps tracking for managing field or remote teams.

To help clients power downstream analytics, Hubstaff offers an application programming interface (API) for clients to extract data on business entities. Here are a few example entities you can extract from the API:

  • Users
  • Organizations
  • Invites
  • Projects
  • Integrations
  • Tasks
  • Activities
  • Application activities
  • Notes
  • Screenshots
  • Time edit logs
  • Url activities
  • Team payments
  • Clients
  • Locations
  • Job site visits
  • Client invoices
  • Team invoices
  • Time off policies
  • Time off requests
  • Attendance schedules
  • Attendance shifts
  • Holidays
  • Job sites
  • Timesheets

You can visit the Hubstaff API Documentation to explore the entire catalog of available API resources and the complete schema definition for each.

As you think about the data you will need for analytics, don’t forget that Portable offers no-code integrations to other similar applications.

Regardless of the SaaS solution you use, it’s important to find a time tracker with robust data available for analytics.

Load: Which Destinations Are Best for Your Hubstaff ETL Pipeline?

To turn raw data from Hubstaff into dashboards, most companies centralize information into a data warehouse or data lake. For Portable clients, the most common ETL pipelines are:

  1. Hubstaff to Snowflake Integration
  2. Hubstaff to Google BigQuery Integration
  3. Hubstaff to Amazon Redshift Integration
  4. Hubstaff to PostgreSQL Integration
Common Data Warehouses
Common Data Warehouses

Once you have a destination to load the data, it’s common to combine Hubstaff data with information from other enterprise applications like Jira, Mailchimp, HubSpot, Zendesk, and Klaviyo.

From there, you can build cross-functional dashboards in a visualization tool like Power BI, Tableau, Looker, or Retool.

Develop: Which Dashboards Should You Build with Hubstaff Data?

Now that you have identified the data you want to extract, the next step is to plan out the dashboards you can build with the data.

As a process, you want to consume raw data, overlay SQL logic, and build a dashboard to either 1) increase revenue or 2) decrease costs.

Replicating Hubstaff data into your cloud data warehouse can unlock a wide array of opportunities to power analytics, automate workflows, and develop products. The use cases are endless.

Now that we have a clear sense of the insights we can create, let’s compare the process of developing a custom Hubstaff integration with the benefits of using a no-code ETL solution like Portable.

Method 1: Building a Custom Hubstaff ETL Pipeline

To build your own Hubstaff integration, there are three steps:

  1. Navigate the Hubstaff API documentation
  2. Make your first API request
  3. Turn an API request into a complete data pipeline

Let’s walk through the process in more detail.

How to Interpret Hubstaff’s API Documentation

When reading API documentation, there are a handful of key concepts to consider.


There are many common authentication mechanisms. OAuth 2.0 (Auth Code and Client Credentials), API Keys, JWT Tokens, Personal Access Tokens, Basic Authentication, etc. For Hubstaff, it’s important to identify the authentication mechanism and how best to incorporate the necessary credentials into your API requests.

Hubstaff allows for OpenID Connect or JWT tokens. An auth code needs to be generated in after login an a request for the token needs to be made to the authentication endpoint.


It’s important to identify the Hubstaff API endpoints you want to use for analytics. Most APIs offer a combination of GET, POST, PUT, and DELETE request methods; however, for analytics, GET requests are typically the most useful. At times, POST requests can be used to extract data as well.

For Hubstaff, the users endpoint is a great place to get started.

Request Parameters

For each API endpoint you would like to use for analytics, you need to understand the method (GET, POST, PUT, or DELETE) and the URL, but there are other considerations to take into account as well. You should look out for pagination mechanics, query parameters, and parameters that are added to the request path.

Hubstaff paginates every listing by default and sorts by creation order, the default page size is 100, it can be overwritten by sending the 'page_limit' parameter.

How Do You Call the Hubstaff API? (Tutorial)

  1. Follow the instructions above to read the Hubstaff API documentation
  2. Identify and collect your credentials for authentication
  3. Pick the API resource you want to pull data from
  4. Configure the necessary parameters, method, and URL to make your first request (e.g. with curl or Postman)
  5. Add your credentials and make your first API call . Here is an example request using curl (without real credentials):
curl -X GET --header 'Accept: application/json' ''

How Do You Maintain a Custom Hubstaff to Redshift ETL Pipeline?

Making a call to the Hubstaff API is just the beginning of maintaining a complete custom ETL pipeline.

Here is a getting-started guide to building a production-grade pipeline for Hubstaff:

  • For each API endpoint, define schemas (which fields exist and the type for each)
  • Process the API response and parse the data (typically parsing JSON or XML)
  • Handle and replicate nested objects and custom fields
  • Identify which Hubstaff fields are primary keys and which keys are required vs. optional
  • Version control your changes in a git-based workflow (using GitHub, GitLab, etc.)
  • Handle code dependencies in your toolchain and the upgrades that come with each
  • Monitor the health of the upstream API, and —when things go wrong— troubleshoot via the status page, reach out to support, and open tickets
  • Handle error codes (HTTP error codes like 400s, 500s, etc.)
  • Manage and respect rate limits imposed by the server

We won’t go into detail on all of the items above, but rate limits are a great example of the complexity found in a production-grade data pipeline.

Hubstaff has an initial rate limit of 1000 requests per hour per application.

When the limit is reached, a 429 HTTP status code is returned.

If you don’t respect rate limits, and if you can’t handle server responses (like 429 errors with a Retry-After header), your pipeline can break, and analytics can become out-of-date.

What Are the Drawbacks of Building the Hubstaff ETL Pipeline Yourself?

You can probably tell at this point that there is a lot of work that goes into building and maintaining an ETL pipeline from Hubstaff to your data warehouse.

If you want less development work, faster insights, and no ongoing responsibilities, you should consider a cloud-hosted ETL solution.

Let’s walk through the setup process for a no-code ETL solution and its benefits.

Method 2: Using a No-Code Hubstaff ETL Solution

No-code ETL solutions are simple. Vendors specialize in building and maintaining data pipelines on your behalf. Instead of starting from scratch for each integration. Companies like Portable create connector templates that can be leveraged by hundreds or thousands of clients.

Step-By-Step Tutorial for Configuring Your Hubstaff ETL Pipeline

Off-the-shelf ETL tools offer a no-code setup process. Here are the instructions to connect Hubstaff to your cloud data warehouse with Portable.

  1. Create an account (no credit card required)
  2. Add a source —search for and select Hubstaff
  3. Authenticate with Hubstaff using the instructions in the Portable console
  4. Select Redshift and authenticate
  5. Set up a flow connecting Hubstaff to your analytics environment
  6. Run your flow to replicate data from Hubstaff to your warehouse
  7. Use the dropdown to set your data flow to run on a cadence

What Are the Benefits of Using Portable for Hubstaff ETL?

No-Code Simplicity

Start moving Hubstaff data in minutes. Save yourself the headaches of reading API documentation, writing code, and worrying about maintenance. Leave the hassle to us.

Easy to Understand Pricing

With predictable, fixed-cost pricing per data flow, you know exactly how much your Hubstaff integration will cost every month.

Fast Development Speeds

Access lightning-fast connector development. Portable can build new integrations on-demand in hours or days.

Hands-On Support

APIs change. Schemas evolve. Hubstaff will have maintenance issues and errors. With Portable, we will do everything in our power to make your life easier.

Unlimited Data Volumes

You can move as much data from Hubstaff to Amazon Redshift as you want without worrying about usage credits or overages. Instead of analyzing your ETL costs, you should be analyzing your data.

Free to Get Started

Sign up and get started for free. You don’t need a credit card to manually trigger a data sync, so you can try all of our connectors before paying a dime.

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