Why does ETL tooling matter?
Once a business hits a certain scale, being data-driven, hiring data engineers, and putting together a data stack is a priority. A fundamental requirement among your data products is an ETL tool. They’re a necessity for analytics and automation.
Data integration solutions like Fivetran and Hevo have out of the box data pipelines that make it easy to extra and load data into your warehouse for analysis. In particular, they will be helpful because their data loading is self-service, transformation and schema features are available, and the data pipelines tend to be more robust and lower maintenance than in-house solutions.
Fivetran is a no-code, cloud-based ELT product with hundreds of integrations built for data teams to extract, load, and transform data from SaaS tools to the data warehouse in five minutes (hence the name, fivetran). The company was founded in 2012 so it has had time to make the integrations it offers more robust and thus lower maintenance.
Hevo Data is a cloud-based ETL, ELT, and reverse ETL solutions for hundreds of data sources as well. The company offers two primary products, Hevo Pipeline and Hevo Activate.
Hevo Pipeline is your classic ELT / ETL tool that moves data from SaaS tools into a data warehouse like Snowflake, BigQuery, or Redshift. Hevo Activate is their reverse ETL product which syncs data from your data store back into SaaS tools such as Salesforce or Google Sheets.
Although on Hevo’s website and on other articles it will claim that Hevo is bidirectional, it is not a true two-way sync. Hevo offers one-way syncs in both directions. But if you are looking to keep your Postgres and Salesforce, for example, in sync with each other such that merge conflicts and data duplication issues are addressed, you will need a solution like Bracket.
Feature Comparison: High-level
As you are evaluating the right automated data syncing solution for your company, the first place you should start is whether or not Fivetran or Hevo supports the source and destination you need to sync. If only Hevo Data supports the connector you care about, this is no longer a Hevo vs. Fivetran conversation, but a Hevo vs. build it in-house conversation. To avoid brittle pipelines and wasted data engineering time, buying is usually better than building. So you can request Fivetran or Hevo to build the connector for you, but odds are that they will only prioritize building it if you are a larger customer.
Fivetran supports over 300 data sources and around 30 destinations. They are definitely a market leader in the data ingestion space. As a closed-source solution, Fivetran builds all of their connectors internally and only some connectors have CDC (change data capture) as a feature.
There is an option for custom connectors, however. Fivetran has cloud functions which enable users to code custom functions and build connectors. It also supports serverless platforms like Azure, AWS Lambda, and Google Cloud where Python, C#, F#, Go, Java, Node.js can be used to write functions.
Hevo has over 150 data sources, around 15 destinations, and supports CDC (change data capture) as a feature. It is a closed-source product that also builds connectors in-house. If Hevo doesn’t have the connector you want, you can request the company to build it but you are most likely out of luck.
Fivetran works well with dbt to support transformations. Fivetran has some existing, common normalizations that work with dbt but these normalizations do not necessarily work with all data connectors. Outside the scope of these quick start data models, you will need to use SQL and dbt more thoroughly to set up transformations bespoke to your use case.
Hevo supports Python-based, drag-and-drop, and automatic. The Python and drag-and-drop transformations are done by the customer. Needless to say, there is more flexibility with the Python-based transformation option than the drag-and-drop option. Hevo does handle some sanitizing and column-naming automatically on it’s own which can be helpful.
Fivetran meets the industry standard security protocols as far as certifications go with SOC II, GDPR and HIPAA compliance. There is also role-based access and permissions to make sure data is safe and not accessible within a company.
Hevo also fulfills the same security certifications: SOC II, GDPR and HIPAA compliance. They encrypt the data (both in-transit and at rest). Hevo also has role-based access — employees at a company can be assigned as a member or an owner. The role-based access has less granularity than Fivetran.
Fivetran is lauded for their support and documentation. There are no training resources for Fivetran.
Fivetran claims to have agent response times of within 1 hour, but you have to be on the premium plans to access this. The higher the pricing tier you are on, the faster the response time. Otherwise you will end up submitting a form on their website and will hear back within a few days. Fivetran does have thorough documentation that is managed entirely internally.
Hevo also has support that varies based on the pricing tier. There is 24/7 email support if you are on the free tier but 24/7 live support if you select the Starter plan. Premium support with a dedicated team is available on the business plan that has custom pricing. Hevo also has documentation and videos to help guide you on using the product.
Fivetran is an ELT solution only which means it will only sync in one direction: from SaaS tools to your data warehouse. For example, you can consolidate all your Salesforce data into a single repository like Snowflake.
Hevo offers ELT, ETL, and reverse ETL. This means you are able to set up one-way syncs from Salesforce to Postgres and separately Snowflake back to Salesforce. Running an ETL / ELT pipeline and a reverse ETL pipeline on the same Salesforce objects and same Postgres tables is not advised. This is bidirectional ETL which Hevo does not handle, despite what other articles may say. Doing this will result in merge conflicts, infinite loops, data duplication (really the worst you can imagine).
If you need to sync bidirectionally (e.g. all updates in Salesforce are reflected in Postgres and vice-versa, in real time) then you can see how to do that here.
Fivetran prices based on monthly active rows. This means any row that is created, updated, or deleted in a given month is an “active” row. So if you have 1 million rows but only 1 row was updated 500 times in a month, then you only pay for that 1 row. Sounds great if the same rows are updated many times. In fact, it tends to be an affordable option with low amounts of data. However, Fivetran does get costly as your data and company scale which is a common complaint and reason people look for alternatives in the first place. It is certainly a premium price point.
The pricing is also hard to predict because it is not clear how many rows of your data will be active in a month, but Fivetran does estimate that 2-18% of all rows will be “active” in a given month — still a wide range to really understand costs.
Fivetran does have a free plan available and has a 14 day free trial on all plans, including the enterprise plan.
Hevo’s pricing is based on the number of events. An event is defined as a record that is updated or inserted in the destination (data warehouse, database, etc.)
Hevo tends to be a cheaper alternative to Fivetran. Pricing ranges from $299 / month to $1449 / month based on the number of events each month (that pricing range is for 5 million to 100 million events). Above 100 million events, you will need to speak to the sales team for custom pricing. Hevo has a free plan of up to 1 million events and has a 14 day free trial.
Both tools are reliable options with enterprise customers and at the end of the day, are very similar.
If you’re looking for very robust ELT-only pipelines with strong documentation at a premium price point, choose Fivetran.
If you’re looking for a more affordable option with ETL and reverse ETL under one hood but with fewer data sources, choose Hevo.
If you’re looking for a true bidirectional ETL with real-time updates and predictable pricing, use Bracket.
Bracket’s bidirectional ETL product keeps SaaS tools and Databases in sync. For example, an update in Salesforce will be reflected in Postgres and vice-versa, without any merge conflicts or infinite loop issues that you would run into by selecting a solution like Matillion that just stacks 2 one-way data pipelines on top of each other.
With a solution like Bracket, you also get unified logging, up to real-time data refreshes, and don’t have to worry about data inconsistency issues that you would have with Matillion or the combination of Fivetran and an additional third party vendor.
You can think of Bracket as a Heroku Connect alternative but for any SaaS and database / warehouse combination.
Interested in learning more about Bracket? Check out our web app and get started!