What Is Reverse ETL?
Understanding The Modern Data Stack
Posted by Alejandro Rusi
on December 14, 2022 · 4 mins read
FAQ: What Is Reverse ETL?
In this post, we’ll cover the basics on the processes of ETL, ELT, and Reverse ETL. The latter is a crucial component of The Modern Data Stack. These are the main questions you’ll be able to answer after reading:
- What Is ETL (Extract, Transform, Load)?
- What Is ELT (Extract, Load, Transform)?
- What Is Reverse ETL?
- Why Is It Relevant?
- What Can Mutt Data Do For Your Data Stack?
What Is Extract, Transform, Load (ETL)?
As the name suggests, ETL consists of extracting raw data from different sources, transforming said data on a secondary processing server, and loading the data into a database (commonly a data warehouse) where a team can later extract insights through analysis for dashboards and reporting.
What is Extract, Load, Transform (ELT)?
Once again, as the name suggests, ELT consists of extracting raw data from different sources. On this occasion the raw data is loaded directly into a cloud warehouse. The transformations don’t occur on a secondary processing server, instead directly inside the data warehouse. Here teams can then use the data, analyze it and produce insights. The principal cause behind ELT is the growth of cloud products like Redshift and Snowflake.
What is Reverse ETL?
In reverse ETL, data is extracted from the data warehouse or data lake, transformed inside that same warehouse (basically meaning it’s changed into the formats needed by the third-party systems used in the company), and then loaded into that third party system for insights, action, etc.
Why Is It Relevant?
Reverse ETL is responsible for enabling teams to access data from different systems using processes and applications that they are familiar with. The process is necessary for teams to be able to act on data in real-time.
The Modern Data Stack facilitates building a single source of truth in a data warehouse. Reverse ETL gets that data out of the warehouse into used tools for day-to-day agile decision-making.
For example, if you want to create an audience, across different paid media platforms, with the people who have added products to their shopping cart but have not purchased. The place to combine this information would be a Data Warehouse. Implementing a Reverse ETL process would allow you to synchronize the audience in your analytical database for all the different marketing destinations.
What Are Some Recommended Reverse ETL Tools?
Grouparoo is an open-source Reverse ETL tool recently acquired by Airbyte (the tool we suggest for ingestion). It's the most active open-source Reverse ETL tool today and has great integration capacities.
If you're looking for a mature option to get you up and running in no time, there are known paid options such as Census and Rudderstack. Both offer free trials with limited functionalities to help users decide.
What We Can Do For Your Stack
Modern Data Stacks, Machine learning, and AI implementations can be quite challenging and failure-prone. Companies spend significant amounts of time and money implementing these solutions.
We’ve climbed the MDS mountain on many occasions - we are experts at planning, organizing, developing, and nurturing the necessary teams, capabilities, tooling, frameworks, and best practices for the climb.
Years of experience have allowed us to develop a sixth sense. We know where to look, we predict unforeseen consequences, and prepare your company for different tracks and needs that you will need down the line in years to come.
We don't believe in one-size fits all solutions: Every business is unique. Working with Mutt means working with an expert team of in-house data engineers, scientists, mathematicians, and business #DataNerds that take the time to understand your specific needs, goals, and constraints.
Our team will analyze where you stand today, what your options are, and the best way to reach your goals, making the best possible use of your resources.
Accelerated Time To Value
Our experience building and implementing Modern Data Stacks for different companies in different industries has led us to a collection of tried and best practices and baseline structures that allow us to leapfrog your developments shortening time to value.
Long-Lasting Solution: Knowledge Transfer & Best Practices
We focus on delivering a robust modern data stack with tech capabilities that last. We don’t simply deliver a product and leave our clients to their own devices. We transfer our knowledge on best practices and processes, upskilling client teams so they can sustain the solution in time and adapt or scale the system if necessary.
Want To Dive Deeper?
Mutt Data can help you crystallize your data strategy through the design and implementation of technical capabilities and best practices. We study your company’s business goals to understand what has to change so we can help you accomplish it through a robust technical strategy with a clear roadmap and set of milestones. Talk to one of our sales reps at email@example.com or check out our sales booklet and blog.