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What is Reverse ETL? The Definitive Guide

Everything you need to know about Reverse ETL.

Tejas Manohar.

Tejas Manohar

Luke Kline.

Luke Kline

April 14, 2023

14 minutes

What is Reverse ETL? The Definitive Guide

Cloud data warehouses have greatly simplified the data landscape, creating a centralized platform where organizations can store and manipulate their data for analytics use cases. However, many companies now want to operationalize this data across their business teams, and this need has given rise to Reverse ETL.

This blog post will discuss what Reverse ETL is, why it’s different from ETL, the core use cases it powers, and why it’s so important.

What is Reverse ETL?

Reverse ETL is the process of copying data from your central data warehouse to your operational systems and SaaS tools so your business teams can leverage that data to drive action and personalize customer experiences.

Data warehouses are only accessible to technical users who know how to write SQL. However, this is often where your core metrics and customer definitions live. For a B2B business, this might include metrics like active workspaces, last login date, churn rate, LTV, lead score, etc. For a B2C business, this might include items in cart, recent purchasers, pages viewed, etc.

Reverse ETL syncing data to Salesforce

Syncing Data to Salesforce

Reverse ETL is all about syncing this data to your downstream tools, thus further unlocking the value of your data warehouse. Instead of reacting to your data as it's persisted into a reporting tool, Reverse ETL allows you to take a proactive approach and put it in the hands of your operational teams so they take action in your business applications.

What’s the Difference Between ETL and Reverse ETL?

Traditional ETL has been around since the 1970s, and for the most part, data pipelines have remained largely unchanged. For those unfamiliar, ETL stands for extract, transform, and load.

Whereas traditional ETL pipelines are a one-way door used to read from a source system and write data to a cloud data warehouse, Reverse ETL pipelines are the exact opposite. Reverse ETL is the process of reading from a warehouse and writing to an operational system like a marketing automation tool or an ad platform. Both methods make use of batch processing. While these two data pipelining techniques sound very similar, there are many technical differences between ETL and Reverse ETL under the hood.

ETL is primarily used to power analytics use cases and consolidate disparate sources into a single unified view, while Reverse ETL is used to power Data Activation use cases. With ETL, you’re merging and loading data into tables based on “updated_at” fields,” and if you make a mistake in this process, you can simply delete the table in your warehouse and re-ingest the data.

ETL pipeline example

The ETL Process

Reverse ETL is slightly different because you’re syncing rows of data from your warehouse to your internal systems. The data structure for objects and fields is much more restricted in a SaaS tool compared to a data warehouse, and you have to be careful not to accidentally overwrite data because most operational tools don’t have an undo or rollback button.

Reverse ETL Pipeline example

The Reverse ETL Process

Additionally, to avoid rate limits and sync failures, you have to deduplicate your data and compare the values of your current warehouse query to what you’ve previously synced. With ETL, where you’re writing to a data warehouse, you don’t have to worry about any of this because warehouses are a lot more flexible.

To summarize, Traditional ETL is focused on data integration and getting data into the warehouse, and Reverse ETL is focused on Data Activation and getting data out of the warehouse.

The Complete Reverse ETL Buyer's Guide

Read our whitepaper and see the most important factors to consider when purchasing a Reverse ETL tool:

  • Integrations
  • Developer features
  • Pricing
  • Implementation time

How Does Reverse ETL Work?

Reverse ETL works by querying against your data warehouse and writing the results of that query to the downstream tool of your choice. Every Reverse ETL tool has four core components, sources, models, syncs, and destinations.

  • Sources represent the location where your business data is stored. Most of the time, this is a data warehouse like Snowflake or Google BigQuery.
  • Models consist of SQL statements that define how your data is represented and what data you want to pull from your source.
  • Syncs allow you to define the data from your model and declare how you want those records to be mapped to the appropriate fields in your end destination.
  • Destinations include any location that you want to send your source data to or where your business users consume this data (e.g., Salesforce, Google Ads, Iterable, Braze, etc.)

Reverse ETL sits as an additional layer on top of your existing data warehouse, allowing you to access and activate all of your existing data models.

Where Reverse ETL fits into the Modern Data Stack

Where Reverse ETL fits into the Modern Data Stack

Why You Need Reverse ETL

Every company wants to be more data-driven. Yet the most daunting question for every organization is “How?" Building dashboards to unlock insights is part one, but the last mile of “analytics enablement” is translating those insights into action.

Data Activation

Analytics enablement is typically seen as a people problem, but how you present data can play an equally significant role. Imagine you're a B2B company trying to figure out which accounts your sales reps should focus their efforts on. In most scenarios, your data analyst would use SQL to derive characteristics of high-value leads and present them to you in a BI report.

The problem is that this data isn't actionable, and to your analyst's dismay, the report is rarely even opened. Instead of forcing your analytics team to train your sales reps to use BI reports, what if you could empower your analysts to feed lead scores from your data warehouse into a custom field in Salesforce? This is the exact type of use case where Reverse ETL excels.

Data Silos

For many companies, the data warehouse ends up being the final resting place for data. As a result, the platform that was designed to eliminate data silos actually just ends up becoming one data silo. Since Reverse ETL moves data out of the warehouse, you have access to every data source and dataset regardless of where that data originated. This means your business users are no longer confined to the data living in their business tools.


Reverse ETL isn’t flashy, but companies are filled with far less glamorous problems when it comes to data. Every organization has tons of manual requests for data floating around:

  • Marketing wants to sync a list of shopping cart abandoners to Google Ads for retargeting.
  • Support wants to search Zendesk for accounts at risk of churning.
  • Accounting wants customer attributes synced to NetSuite.
  • Finances wants a CSV of transaction data to use in Excel or Google Sheets.
  • Sales wants access to product usage in Salesforce.
  • Product wants to be notified in Slack when customers enable a specific feature.

How Reverse ETL powers business teams

How Reverse ETL powers business teams

In order to address each of these requests, your data team has to build and maintain a custom integration with various APIs or manually download an ad-hoc CSV file for each request that comes in.Implementing a Reverse ETL tool avoids these problems because data flows out of your warehouse automatically. This means your data team can focus on higher-value problems like optimizing your infrastructure costs or unlocking new insights and building custom data models.

Reverse ETL Use Cases

While Reverse ETL completely removes the burden from engineering teams, it also unlocks a variety of use cases across business teams so you can drive more value with your data.

Marketing Teams

Figuring out how to increase match rates within ad platforms, optimize return on ad spend (ROAS) and decrease customer acquisition costs (CAC) is a top priority for every marketing team. With Reverse ETL, you can define custom audiences in your warehouse and sync them to any of your marketing channels. You can also use those same audiences in your lifecycle marketing campaigns to improve your personalization based on the unique historical and behavioral data of your customers.

Sales Teams

Your sales team wants and needs access to the unique behavioral data and product usage data in your warehouse (e.g., workspaces, last-login date, active users, page views, etc.) With Reverse ETL, you can send this data directly to your CRM, so your sales team can have a holistic view of your customer and take action in real-time. You can also use Reverse ETL to send notifications to external tools like Slack to notify your sales reps when customers or users take specific actions in your product/app.

Product Teams

The key to improving your product and driving adoption is experimentation and optimization. However, in order to power your customer-facing use cases, you need to sync customer data to your production database to optimize your on-site personalization. With Reverse ETL, you can send customer attributes to your production database so you can serve customized experiences that feel unique to each individual user. This could be doing something as simple as showing billing information within your app or offering a special coupon to your most loyal customers.

Support Teams

Prioritizing the right tickets and reducing churn should be the end goal of every customer success team. Reverse ETL allows you to sync key metrics like LTV, ARR, and churn rate to your support tool so your success teams can prioritize tickets with the highest impact.

Reverse ETL vs. Other Technologies

Reverse ETL is not a new concept by any means. Companies have been trying to activate their data for years, and many other technologies have tried to solve this problem.

Point-to-Point Solutions

Reverse ETL is not a new concept by any means. Companies have been trying to activate their data for years, and many other technologies have tried to solve this problem.

Integration Platform as a Service (iPaaS) technologies like Zapier, Tray, and Workato can be attractive options for tackling Reverse ETL use cases because they let you send data from one platform to another.

Unfortunately, this creates an intricate web of pipelines and complex workflows that aren't scalable. If you have four applications, you’ll quickly find yourself with 16 potential pipelines (4x4 = 16). In order to even have data flow, you have to weave in various dependencies and if/then clauses into every workflow.

Reverse ETL creates a hub-and-spoke approach where all of your data flows in and out of your single source of truth (e.g., the data warehouse).

Hub-and-Spoke Architecture

Point-to-Point vs. Hub & Spoke

Customer Data Platforms

You're probably familiar with customer data platforms (CDPs.) Platforms like Segment have made a name for themselves in the data and marketing world by creating a single platform where you can store all your customer data and operationalize it across your various systems.

The problem is these platforms often only have access to clickstream event data, and getting access to relevant first-party data is challenging. CDPs operate as their own separate entity, which means they store data outside of your infrastructure, which can have significant implications around GDPR, CCPA, and HIPAA.

Additionally, CDP implementations can take upwards of a year, and that’s not even accounting for the onboarding time it takes to train your teams on how the tool works. These platforms also impose instructions on how your data can be stored and modeled, usually requiring everything to fall within user and account objects.

They also place restrictions on how long you can access historical data, and you inevitably end up paying for an additional layer of storage even though all of the data you need to power your customer-facing use cases already lives in your data warehouse, to begin with.

Reverse ETL tools aren’t encumbered with these limitations because they operate and integrate with your existing tools and technologies. With Reverse ETL, you’re never storing data, you’re simply reading from your warehouse and writing the results of that query to your destination. This creates a Composable CDP architecture on top of your existing data warehouse, giving you increased flexibility to uniquely solve your use cases

Best Reverse ETL Tools

While there are many different data integration tools, there aren’t actually that many companies specializing in Reverse ETL. Here’s a quick summary of the top three companies solving Reverse ETL.

  • Hightouch: Hightouch is a Reverse ETL platform that is designed for data teams and marketing teams. The platform supports 150+ destinations, and it integrates with a variety of data tools like dbt, Fivetran, Looker, etc. It offers version control, a live debugger, and support for alerting. For non-technical users, Customer Studio provides a no-code option so your business teams can self-serve and granularly build audiences using the parameters your data team has set in place
  • Census: Census is a Reverse ETL platform that offers a number of features for moving data from your warehouse to numerous destinations, but it’s not quite as flexible as Hightouch when it comes to developer-friendly and marketing-friendly features.
  • Segment: Segment is a traditional CDP. However, the company recently dipped its toes into Reverse ETL and is now offering warehouse-first capabilities. Many of the features end up being tightly coupled with the platform’s existing CDP offerings.

Build vs. Buy

If you've ever bought enterprise software, you'll know there are always pros and cons to purchasing a purpose-built solution and building one in-house. If you're leaning toward the DIY camp, you'll most likely need spare data engineering resources (good luck finding any).

Building custom Reverse ETL pipelines can become complicated very quickly. Every third-party API is constantly updating and changing, so you'll either have to download/upload manual CSV files or build a unique integration for every tool in your data stack.

Third-party APIs and CSVs

Third-party APIs & CSVs

You'll also have to monitor and manage each integration because a single API change can break your entire data flow, and this isn't even mentioning all of the other factors you have to consider: authentication, batching, rate limits, field mapping, parallelizing, error handling, monitoring, etc.

Buying a fully managed Reverse ETL tool completely solves all of these problems, because Reverse ETL platforms take on the cumbersome problem of managing API integrations. Rather than worrying about all of these underlying issues, Reverse ETL tools enable you to automate and schedule your data syncs. They also provide you with a visual interface where you can easily map the fields from your source to your destination.

Reverse ETL tools are declarative, which means you can simply declare how your data should appear in your end destination, and you’re in complete control over how frequently your syncs run. Reverse ETL establishes what’s known as a write once, use anywhere architecture, enabling you to send the same data to multiple destinations while also managing all of your syncs in one central platform.

Syncing data to multiple destinations

Write once, use anywhere

Final Thoughts

Reverse ETL solves the last-mile problem in the modern data stack, and it unlocks the value of your data warehouse for your entire data lifecycle. Reverse ETL democratizes the data that was once only available to your technical users, and it ensures that everyone across your organization has access to the same core definitions of your customer in your downstream systems.

If you prefer investing in best-in-class tools and want to have a fully managed Reverse ETL solution up and running in a matter of minutes, signup for a Hightouch workspace today or schedule a demo!

The Complete Reverse ETL Buyer's Guide

Read our whitepaper and see the most important factors to consider when purchasing a Reverse ETL tool:

  • Integrations
  • Developer features
  • Pricing
  • Implementation time

More on the blog

  • ETL vs. Reverse ETL: The Technical Differences.

    ETL vs. Reverse ETL: The Technical Differences

    Discover the technical differences between Reverse ETL and ETL/ELT and learn how they work behind the scenes.

  • What is Data Activation?.

    What is Data Activation?

    Learn everything to know about Data Activation, what it is, why it matters, and how you can get started activating your data today.

  • What is a Composable CDP?.

    What is a Composable CDP?

    Learn why Composable CDPs are seeing such rapid adoption, how they work, and why they're replacing traditional CDPs.


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