Sold by: Hevo Data
Hevo is the trusted choice of over 2,500 data teams across over 40 countries to replicate data from all their sources into a cloud data warehouse. Using Hevo, you can set up a data pipeline in just 3 simple steps and replicate data in as little as 5 minutes. Moreover, Hevo's CDC (change data capture) feature ensures that any changes made to data sources are automatically updated in the warehouse. Hevo automates schema management; any changes in the source schema are automatically updated in the destination schema, eliminating the need for manual schema management. Hevo also includes built-in pre-load and post-load transformation capabilities. The pre-load transformation formats and cleans the data on the fly, while the post-load transformation allows you to run SQL-based transformations and dbt Core models in sync with your pipelines on the data warehouse.
4.4
Overview
Hevo is a zero-maintenance data pipeline platform that automatically syncs data from 150+ data sources, including SQL, NoSQL, and SaaS sources, to Redshift and other cloud warehouses and transforms it for analytics - saving data teams from the manual headache of managing pipelines.
Hevo is trusted by over 2500 data teams across more than 40 countries to integrate all their data into a warehouse. With its simple and intuitive interface, setting up data pipelines on Hevo is a breeze; it takes just 3 simple steps and only 5 minutes. Plus, Hevo's CDC (change data capture) feature ensures that any changes made to data sources are automatically updated at the destination.
One of the key advantages of Hevo is its automated schema management, which automatically changes the destination schema as your source schema evolves or changes. This eliminates the need for manual intervention to update schemas. Hevo also comes with in-built pre-load and post-load transformation capabilities. The pre-load transformation formats and cleans the data on-the-fly and the post-load transformation automatically runs models (also supports dbt Core projects) to prepare the data for analytics. All of this saves hours of engineering effort for data teams in manually integrating and transforming data.
Hevo offers transparent usage-based pricing. For pricing visit https://hevodata.com/pricing/consumption/ .
Highlights
- End-to-end Automation - Hevo automates the entire ELT process, from integrating data into the warehouse to transforming it for analytics.
- Highly Reliable - Hevo offers 100% data accuracy, 99.9% uptime, and low latency and easily scales without any impact on performance.
- Fully Secure - Hevo complies with HIPAA, SOC 2, and GDPR and offers secure connection options like SSH, Reverse SSH, and VPN.
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Dimension | Description | Cost/month | Overage cost |
|---|---|---|---|
Starter Plan | Pay-As-You-Go, compare plans at hevodata.com/pricing/consumption | $0.01 | |
Business Plan | Pay-As-You-Go, compare plans at hevodata.com/pricing/consumption | $0.01 |
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Hevo is the trusted choice of over 2,500 data teams across over 40 countries to replicate data from all their sources into a cloud data warehouse. Using Hevo, you can set up a data pipeline in just 3 simple steps and replicate data in as little as 5 minutes. Moreover, Hevo's CDC (change data capture) feature ensures that any changes made to data sources are automatically updated in the warehouse. Hevo automates schema management; any changes in the source schema are automatically updated in the destination schema, eliminating the need for manual schema management. Hevo also includes built-in pre-load and post-load transformation capabilities. The pre-load transformation formats and cleans the data on the fly, while the post-load transformation allows you to run SQL-based transformations and dbt Core models in sync with your pipelines on the data warehouse.
Streamkap CDC is streaming change data capture for real-time database replication and in-stream processing. Get sub-second latency to power amazing customer and employee experiences.
Customer reviews
Consumer Goods
Hevo is flexible, powerful, and backed by excellent support
Reviewed on May 28, 2026
Review provided by G2
What do you like best about the product?
Its technical possiblities, flexibility and customer service / support.
What do you dislike about the product?
There are some limitations, such as a lack of some built-in connectors (e.g. RTB House, Yext, Bing Webmaster, Google My Business). Also, it would be awesome if Hevo can offer reverse ETL as well.
What problems is the product solving and how is that benefiting you?
Using Hevo HEMA is able to easily import data from the various marketing channels on an automated basis.
Fernand R.
Seamless MongoDB to BigQuery Integration with Exceptional Support
Reviewed on May 27, 2026
Review provided by G2
What do you like best about the product?
I really appreciate the customer service from Hevo Data. Setting up the pipeline is really easy, which makes the process straightforward. Whenever there's trouble, the customer service is there to help. Hevo Data is also smart enough to replicate complex nested data structures from MongoDB in a good way to BigQuery. The initial setup process is quite simple because you just need to whitelist Hevo Data on your side, input credentials, and specify what to replicate and how often, and then Hevo Data handles the rest. It's really well made.
What do you dislike about the product?
I can't identify something which could be better at Hevo Data, to be honest. Maybe a clearer billing. Also, maybe better orchestration possibilities, especially with DBT, but I heard they are working on it.
What problems is the product solving and how is that benefiting you?
Hevo Data solves the problem of replicating complex nested structures from MongoDB to BigQuery effectively. It's reliable and good at mimicking data structure.
Marketing and Advertising
Fast, Helpful Support with an Easy-to-Use UI and Solid Performance
Reviewed on May 26, 2026
Review provided by G2
What do you like best about the product?
The best thing about Hevo is the fast and helpful customer service. The UI is easy to use and performance is never an issue. Pricing is good compared to other tools as well.
What do you dislike about the product?
Wish there was a way to modify the pipelines after creations on most of the sources
What problems is the product solving and how is that benefiting you?
A high functioning elt tool that lets us split out by accounts easily and is updated fast after sources change their apis
Information Technology and Services
Worry-Free Pipeline Maintenance Made Easy
Reviewed on May 26, 2026
Review provided by G2
What do you like best about the product?
It handles pipeline maintenance for me, so I don’t have to worry about it.
What do you dislike about the product?
I would prefer it if there were a learning plan available for this.
What problems is the product solving and how is that benefiting you?
Data pipeline automation, which can sometimes be difficult to maintain.
Nikhil K.
Powerful Automated Pipeline with Flexible Selection, Smooth Integrations, and Fast Support
Reviewed on May 05, 2026
Review provided by G2
What do you like best about the product?
Experienced a powerful automated pipeline that offers flexible object selection, effectively cutting costs.
Enjoy a user-friendly interface paired with quick and reliable support to enhance your productivity.
Integrations are simple and easy to identify the required objects and pipeline.
I can monitor the performance without lag.
Enjoy a user-friendly interface paired with quick and reliable support to enhance your productivity.
Integrations are simple and easy to identify the required objects and pipeline.
I can monitor the performance without lag.
What do you dislike about the product?
A video tutorial would be helpful for any new user rather than reading documents.
Also, if Hevo could ingest a materialized view to BigQuery, it would be helpful.
Also, if Hevo could ingest a materialized view to BigQuery, it would be helpful.
What problems is the product solving and how is that benefiting you?
Hevo ingests the data from our server to BigQuery, where we directly pick up the required field data after creating a materialized view.
This helps in real-time reporting through Data Studio dashboards.
All the historical data helps us when we perform AB testing.
This helps in real-time reporting through Data Studio dashboards.
All the historical data helps us when we perform AB testing.