Access your data on ActiveCampaign

The first step in loading your ActiveCampaign data to any kind of data warehouse solution is to access your data and start extracting it.

ActiveCampaign has a well-designed API (here) which is structured around REST, HTTP, and JSON, sufficient for interacting with the platform programmatically. API endpoint URLs are organized around resources, such as connections or deals. The available resources include the following:

1. Users
2. Deal
3. Pipelines
4. Deal Stages
5. Deal Tasks
6. Deal Task Types
7. Organizations
8. Connections
9. E-commerce Customers
10. E-commerce Orders

In addition to the above, the things that you have to keep in mind when dealing with the ActiveCampaign API, are:

1. Rate limits. There is no restriction regarding rate limits in v3 of the API which is currently on beta. However, the older version describes the rate limits as 5 requests per second per account.
2. Authentication. You can authenticate on ActiveCampaign with simple token authentication using the user’s API key in the request header.
3. Pagination. API endpoints that return a collection of items are always paginated. The number of results to display can vary with a maximum value of 100.

Prepare your ActiveCampaign data for Amazon Redshift

After you have accessed your ActiveCampaign data, you will have to transform it based on two main factors,

1. The limitations of the database that the data will be loaded onto
2. The type of analysis that you plan to perform

Each system has specific limitations on the data types and data structures that it supports. If for example, you want to push data into Google BigQuery, then you can send nested data like JSON directly.

Of course, when you are dealing with tabular data stores, like Microsoft SQL Server, this is not an option. Instead, you will have to flatten out the data, just as in the case of JSON, before loading into the database.

Amazon Redshift is built around industry-standard SQL with added functionality to manage very large data sets and high-performance analysis. So, in order to load your data into it, you will have to follow its data model which is a typical relational database model. The data you extract from a data source should be mapped into tables and columns where you can consider the table as a map to the resource you want to store and columns the attributes of that resource.

As data are probably coming in a representation like JSON that supports a much smaller range of data types you have to be really careful about what data you feed into Redshift and make sure that you have mapped your types into one of the datatypes that are supported by Redshift. Designing a Schema for Redshift and mapping the data from a data source to it is a process that you should take seriously as it can both affect the performance of your cluster and the questions that you can answer. It’s always a good idea to have in your mind the best practices that Amazon has published regarding the design of a Redshift database.

Again, depending on the system that you will send the data to and the data types that the API exposes to you, you will have to make the right choices. These choices are important because they can limit the expressivity of your queries and limit your analysts on what they can do directly out of the database.

It’s always a good idea to have in your mind the best practices that Amazon has published regarding the design of a Redshift database.

Designing a Schema for Redshift and mapping the data from your data source to it is a process that you should take seriously as it can both affect the performance of your cluster and the questions that you can answer. It’s always a good idea to have in your mind the best practices that Amazon has published regarding the design of a Redshift database. When you have concluded on the design of your database you need to load any data on one of the data sources that are supported as input by Redshift, these are the following:

• Amazon S3
• Amazon DynamoDB
• Amazon Kinesis Firehose

How to Load data from ActiveCampaign to Redshift

To upload any data to Amazon S3 you will have to use the AWS REST API. APIs play an important role in both the extraction but also the loading of data into our data warehouse. The first task that you have to perform is to create a bucket, you do that by executing an HTTP PUT on the Amazon AWS REST API endpoints for S3.

You can do this by using a tool like CURL or Postman. Or use the libraries provided by Amazon for your favorite language. You can find more information by reading the API reference for the Bucket operations on Amazon AWS documentation.

After you have created your bucket you can start sending your data to Amazon S3, using again the same AWS REST API but by using the endpoints for Object operations. As in the Bucket case you can either access the HTTP endpoints directly or use the library of your preference.

Amazon Redshift supports two methods for loading data into it. The first one is by invoking an INSERT command. You can connect to your Amazon Redshift instance with your client, using either a JDBC or ODBC connection and then you perform an INSERT command.

The way you invoke the INSERT command is the same as you would do with any other SQL database. For more information, you can check the INSERT examples page on the Amazon Redshift documentation.

Redshift is not designed for INSERT-like operations, on the contrary, the most efficient way of loading data into it is by doing bulk uploads using a COPY command.

You can perform a COPY command for data that lives as flat files on S3 or from an Amazon DynamoDB table. When you perform COPY commands, Redshift is able to read multiple files in simultaneously and it automatically distributes the workload to the cluster nodes and performs the load in parallel.

What is the best way to load data from ActiveCampaign to Redshift and what are the possible alternatives?

So far we just scraped the surface of what can be done with Amazon Redshift and how to load data into it. The way to proceed relies heavily on the data you want to load, from which service they are coming from, and the requirements of your use case.

Things can get even more complicated if you want to integrate data coming from different sources.

A possible alternative, instead of writing, hosting and maintaining a flexible data infrastructure, is to use an ETL as a service product like RudderStack that can handle this kind of problems automatically for you.

RudderStack integrates with multiple sources or services like databases, CRM, email campaigns, analytics and more. Quickly and safely move all your data from ActiveCampaign to Redshift and start generating insights.