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[Part 3.2] 3 (more) key considerations for evaluating the best reverse ETL tool

Allie Beazell is director of developer marketing @ Census. She loves getting to connect with data practitioners about their day-to-day work, helping technical folks communicate their expertise through writing, and bringing people together to learn from each other.

​​This is the final part of our series on evaluating reverse ETL tools. You can read part one here, part two here, and part 3.1 here. We’ve also created a comprehensive resource to help you find the best reverse ETL tool, which you can find here.

In this installment, you’ll learn three (more) key things you should consider as you evaluate reverse ETL solutions, including:

  • SQL fluency and ease of use 🤗
  • Ongoing community & vendor support 🤝
  • Transparent pricing 💰

To wrap things up, we’ll also discuss some next steps for setting yourself up for success with reverse ETL. 🚀

In the final installment of our series on evaluating reverse ETL tools, we’re narrowing in on three more key considerations you should use to grade your options for reverse ETL.

Up to now, we’ve talked about why reverse ETL is such a key part of today’s modern data stack, why you really, really, really don’t want to build reverse ETL tooling yourself, and four other key considerations to measure vendors against.

As we wrap up the series, we hope that you’ve seen the potential of reverse ETL tools to unite your data and business teams to achieve operational analytics (which is a fancy way of saying you can do more with your data in the frontline business tools--like Salesforce, HubSpot, Marketo, and Braze--you and your customers rely on).

Without further ado, let’s take a look at the final three key considerations to keep in mind as you choose the best reverse ETL tool for your use case. If you diligently compare each option against these criteria, you’ll end up with a reverse ETL platform that supports your business today, and into the future.

1. SQL fluency and ease of use 🤗

If you’re like us, you’re always looking for best-in-class tooling that doesn’t just make your data better but your life easier, too. Reverse ETL can do that with an intuitive user interface and SQL fluency to make it accessible to anyone on your team with SQL knowledge. Both these qualities are a giant step toward self-service and data democratization.

Here’s what we mean by ease of use and SQL fluency, as well as some additional usability considerations to keep in mind as you evaluate.

  1. Your reverse ETL tool should speak SQL. This means anyone on your team that speaks SQL can create sync and start activating data in the warehouse with ease. This helps you tap into the talented people within your organization immediately--whether they’re a data analyst, data engineer, data scientist, or ops unicorn in sales, marketing, or finance.
  2. Your reverse ETL tool should be easy to use. There shouldn’t be any headaches to figuring out how to create and manage syncs. Your tool should have an intuitive UX that makes it easy to create connections to data sources and destinations and easily map the data you need with point-and-click data mapping.
  3. Your reverse ETL tool should let you flexibly create SQL models. You should be able to easily create a SQL model to define logic and data structure for your syncs, whether that’s in your cloud data warehouse as tables or views, natively in the reverse ETL tool itself, or as a dbt model. This includes:
  4. The ability to specific models as tables or views in your data warehouse.
  5. The ability to define SQL models inside the tool.
  6. The ability for non-technical users to self-serve and move data to their tools.
  7. Native dbt integration. (Bonus: Your reverse ETL tool should allow you to re-trigger your syncs when your model updates (e.g. when you add a new column to your model))

If your new reverse ETL tool ticks all of the boxes above, you and your team are off to a great start to doing more with your data from day one. After all, the best reverse ETL tool should help elevate the skill sets and insights of every member of your team. Data for one, data for all.

2. Ongoing community & vendor support 🤝

Try as any vendor may, there will be times that troubleshooting is necessary (or just times that your or your team have questions about best practices to become better reverse ETL power users). It’s during these times that ongoing community and vendor support are important.

Vendors and the communities that they maintain should offer support not just for their product but the most common API integrations they work with. After all, unlike ETL tools which sync from business systems into the warehouse as a destination, syncing back into business tools exponentially increases the number of questions, issues, and quirks folks can run into.

Beyond receiving alerts and having great docs to help you solve issues yourself, high-quality support and community help you trust your vendor’s team and learn more in the process.

To ensure that your future reverse ETL vendor offers the support and reassurance you need to get help when something goes awry and uplevel your skills as the industry changes, focus on the following four things when evaluating the company:

  1. A demonstrated commitment to keeping SLAs. Downtime SLAs of at least 99.99% show your vendor takes availability seriously and will make all efforts to keep service running for you, this could even include downtime compensation.
  2. Highly available support & in-app support. This basically just means how easy it is to get a hold of someone when you need to, either on a call or via support functionality. For instance, at Census we hired multiple former heads of data to staff our support team as customer data architects. This role is available as a resource throughout every stage of data your data journey (pre-sales to post success).
  3. Publicly available data experts. Expert knowledge doesn’t do any good if it’s guarded. Your vendor should regularly contribute their expertise to the community in public channels so that you can get more value out of using their tool.
  4. High-quality, public documentation. Your reverse ETL tool shouldn’t be a black box, and this means your vendor should maintain an easy-to-understand and easy-to-navigate library of documentation to turn to when you have questions.
  5. Community engagement. The world of data changes quickly and often. Your reverse ETL vendor should be active in the data communities you care about and available to answer your questions, whether it’s about your data career or your tooling.

At the end of the day, the human experience you have with a reverse ETL vendor is just as important as the power of the product they build. A great product out-of-the-box will certainly get you started, but the work of the humans building it will sustain your future data wins.

3. Transparent pricing 💰

Now to everyone’s favorite part: Pricing. Different reverse ETL vendors charge differently for their tooling and break down pricing models in a variety of ways. As such, it’s important that you find the pricing model that makes the most sense for your specific use case. We asking yourself three questions as you evaluate different pricing models:

  1. How transparent is the pricing model?
  2. Will this scale as my organization grows?
  3. Is it easy for me to calculate my bill 6 months from now?

Most vendors will offer a tiered pricing model, and this is where transparency really matters. Unfortunately, this guide isn’t a fortune teller and only your team can answer those questions to determine which pricing model is best for you. However, here’s a breakdown of the most common pricing models you’ll see:

  • Consumption-based pricing. This model is based on the number of rows synced. Because of the one-to-many relationship of syncs (e.g. the same data is being synced into several different tools) this pricing model can be prohibitive to your organization's growth and get expensive quickly.
  • Connector-based pricing. In our opinion, connector-based pricing offers much more flexibility than consumption-based pricing. It’s more tightly coupled with the value you’re getting out of the tool. However, as your company adds more and more apps, you may quickly grow out of this model.
  • Field or sync-based pricing. This is the most flexible and scalable pricing model for the majority of companies. Pricing based on fields or syncs as it directly reflects how much you’re operationalizing your data (you’re not underutilizing or running up against what you’re paying for in this model). We believe this model is the most transparent and predictable as fields and syncs won’t dramatically change without your awareness, they’re easy to keep track of, and they don’t require pricing add ons to leverage.

As we said, there isn’t a hard and fast answer to what pricing model is best for you and your use case. The most important thing is feeling confident that your vendor’s pricing will support (and not limit) your organization’s increasing demands for data.

Set yourself up for success with reverse ETL 🚀

Choosing a new SaaS tool is never easy, but we hope this guide makes the journey a little less intimidating for reverse ETL. As you work your way through this process, remember: You're making an investment in operationalizing your data and empowering many more people in your organization to use real-time data in their day-to-day. Take it from Canva who used reverse ETL to improve email personalization for over 55M+ users, Bold Penguin who decreased support times by 98% from 24 hours to 30 mins or Figma who improved their sales discovery calls by 10x.

Both you and your business stakeholders are probably feeling real pain, and you have an opportunity to relieve a lot of that pain with the addition of a dedicated reverse ETL tool. Whether the pain stems from your customer support teams spending 30 minutes running a separate BI report to understand customer billing or your sales teams struggling to find the dashboard to understand their accounts product usage, this guide will help you find the right tool to help everyone do more with data ASAP. Just remember to keep the communication lines open between the data team and the business team as you explore the use cases for this exciting new tool.

As a summary of some of the key points to keep in mind:

✅ Consider both connector depth and breadth when thinking about quality

✅ Make sure you feel comfortable with your vendor’s security standards, and that data stays in your environment

✅ Your tool should alert you if anything goes wrong and help you understand how to fix it. Quality support and expertise from your vendor can be really valuable here too.

✅ It should be easy to get started with a fast time to value

✅ Predictable pricing model that scales with your organization

You’ve made it to the end of our reverse ETL evaluation series. 🎉  Before you go out into the wild world of data tooling, make sure to grab our Reverse ETL evaluation checklist. It summarizes all the key considerations we’ve discussed in this series in a TL;DR format that you can share with your team as you choose the best reverse ETL tool for you.

Of course, if you have any questions, or just want some advice on what tools work best for which use case, drop us a line at

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