What is our primary use case?
My main use case for
Hevo is moving data from a series of different databases into a
Snowflake data warehouse.
I can give you a specific example of how I use Hevo to move data between databases and Snowflake. We had one software application that had over 500 customers; however, that application, even though it was a SaaS app, had one Azure SQL Server database per customer, and in those databases, there were four different schemas. I needed to get that data from that application, as well as data from other applications using different databases, different public clouds, and different infrastructure into Snowflake. Using Hevo, I tested that it worked well to move data, made four pipelines for one database manually, and then scripted that using the Hevo API to create effectively 2,000 pipelines for this one application. We had all the data from 500 Azure SQL Server databases with a similar structure into a single Snowflake data warehouse, transforming some of the data to prevent it from overwriting itself from all the different customers.
This specific example illustrates how I effectively used Hevo for that application with 500 Azure SQL Server databases, four different schemas in each database, making 2,000 Hevo pipelines, turning on change tracking in the source database, specifying the tables and fields needed, mapping it out to our destination data warehouse in Snowflake, and letting those pipelines run.
What is most valuable?
The best features Hevo offers are its simplicity and the ability to get started very quickly. You select your source database, select your destination database, pick the fields and tables that you're interested in, and can start moving data very quickly. Hevo has a lot of built-in documentation that helps you know which IP addresses to whitelist and how to turn on change tracking or configure databases like Postgres or
MySQL for binary logging. It's very easy to get started with Hevo. I also love that it allows about a million or maybe even 10 million transactions a month for free, making it really easy to begin using. That's probably my favorite aspect of Hevo; it's simple and fast to get started, allowing for effortless data movement between databases. Within one hour, you can be very productive.
The simplicity and fast setup of Hevo significantly benefited my team and organization because we didn't run into challenges while getting started, although we did hit some limits later. We managed to get started very quickly without any challenges. That simplicity and fast setup were crucial as we struggled with other tools that were costly and complicated. We tried to work out how to use AWS tools to get data from some databases, but many of their options weren't available via the GUI, requiring extensive scripting knowledge. Hevo enabled us to sign up and seamlessly go through the steps of connecting our source database and setting up our destination. While other products had complexity and high costs, Hevo made it super easy to get started and moving.
The documentation of Hevo was good, providing clear step-by-step guidance on what to do for specific source or destination systems to be ready for moving data around.
Hevo positively impacted my organization by allowing us to move data quickly and easily, enabling us to focus on our real challenge: performing analytics and reporting out of Snowflake with all customer data centralized despite using various applications. Hevo allowed us to prioritize our analytical work and minimized my time spent on data movement, which typically is a complicated and lengthy process.
I don't have specific metrics or numbers, but I can say we saved time because we were struggling with other products; we had spent weeks trying to work out AWS Glue and other tools. With Hevo, we got it done quickly, saving a massive amount of time in setup, testing, and going live. It let us focus on analyzing data instead of moving it. Although I don't have quantifiable metrics, it's clear that it saved us considerable time, and while it didn't impact employee needs, it definitely freed up significant resources.
What needs improvement?
Hevo could be improved as we hit limits, particularly when it couldn't keep up with the high number of databases we wanted to sync frequently—ideally updating everything hourly for near real-time analytics rather than a day behind. We found that with many pipelines, performance degraded. After discussing with Hevo engineers, I learned that Hevo is designed for fast individual pipelines, but struggles with many concurrent pipelines. They suggested that consolidating data from fewer pipelines with more fields would perform better, but even that failed when I tested it with a Business Central database that had numerous fields. Hevo does have limits on the number of pipelines it can manage concurrently and on the number of fields in a single pipeline.
Additionally, the API was slower to release compared to the user interface and was not feature-complete, which was frustrating. That said, Hevo actively worked on bridging many gaps. Overall, these were significant pain points I encountered.
For how long have I used the solution?
I have been using Hevo for four years.
What do I think about the stability of the solution?
Hevo is stable.
What do I think about the scalability of the solution?
Hevo's scalability is effective to a point; it scales well with a small number of pipelines but struggles with a large number of concurrent pipelines.
How are customer service and support?
I found Hevo's customer support to be good, and their support team was always friendly.
How was the initial setup?
My experience with pricing, setup cost, and licensing for Hevo was awesome. We found it super cheap to start with; during the free trial, we received 14 days free and could begin using it right away, pushing a lot of data through it. Even once we transitioned to a paid model, it remained cost-effective, allowing us to process well over a million transactions at no charge monthly, and then it was about $50 for millions of transactions. We never paid more than one or $2,000 a month while drawing data across numerous sources. Hevo's pricing, setup cost, and ongoing costs were tremendous, which also led us to lock in an annual plan for about $13,000. We got great value from it, especially when comparing it to competitors whose annual costs were significantly higher, and that didn't include additional operational expenses for self-hosting other solutions.
I don't have precise metrics, but I can say we saved time with Hevo, getting started quickly. We spent several weeks trying to make alternate products work, but with Hevo, we were up and productive within an hour, which saved us a substantial amount of time. The ongoing maintenance was minimal, so we could focus on analytical and reporting tasks without needing to consider the data movement logistics. Hevo facilitated that process, but I don't have any quantifiable numbers.
Which other solutions did I evaluate?
Before choosing Hevo, we evaluated other options like
AWS Glue,
Azure Data Factory, Matillion,
Fivetran, and
dbt Labs.
What other advice do I have?
Hevo did not have any AI capabilities when I was using it, but I think its security is good, utilizing proper web authentication techniques with encrypted keys. However, it does not enforce governance but does provide the means to govern if desired.
Hevo didn't have any AI capabilities, so I cannot comment on its accuracy and reliability of output.
Hevo is deployed in my organization as a SaaS application on whatever infrastructure Hevo operates, which I assume is the public cloud.
My advice for others looking into using Hevo is to use it to test out your concept. Hevo is a great tool for that purpose.
I would rate this product a 7 out of 10.
