Hevo Reviews

Ingesting data is quick and easy. I was able to ingest all our production data and start analyzing within hours. Data modeling using SQL or dBT enables engineers and analyst to create curated datasets usable by others. Provides coding capabilities to customize the data ingestion and model building. Great customer support with knowledge to address your questions. AM team that partners with you.

Would like to add descriptions and documentation to certain objects. More robust scheduling capabilities to align with our business processes.

data ingestion without having to be a software engineer. I've opened up this tool for analyst in our Marketing and CS departments so they can get to the data they need without having to wait for prioritization within the data team

Hevo has been a game-changer for our data integration needs. The platform's user-friendly interface makes it stand out, especially with its standout features like custom SQL-based database pipelines and inbuilt Python-based transformations. These functionalities have significantly streamlined our data processing, enabling us to handle complex tasks with ease.

One of the standout aspects of Hevo is its exceptional customer support. The 24/7 tech support team is not only highly responsive but also incredibly adept at diving straight into any issues that arise. Their quick resolutions have been instrumental in maintaining our operations seamlessly.

Moreover, the onboarding experience with Hevo was remarkably smooth. The platform's intuitiveness made the initial setup hassle-free, allowing us to get up and running in no time.

Another highlight of Hevo is its pricing structure, which is among the best in the market. Comparing it to similar tools, Hevo offers incredible value for its features and functionalities. It's been a cost-effective solution without compromising on quality or performance.

Overall, Hevo has become an indispensable part of our data infrastructure. Its ease of use, powerful features, responsive support, and competitive pricing make it a top choice for any organization seeking efficient data integration and transformation solutions.

Limited sources and destinations on both ETL and reverse ETL.

Low cost ETL solution for data warehousing.

Cost and stability. We dont find any issue so far using it for almost 3 years. Its very reliable and hardly had any issue

Support is not 24 hours so sometimes its not easy during working PST hours. But they are improving and adding new support in progress

We use Hevo for our ELT from many business application including mysql and mongodb to Snowflake

easy to set up , document , support team

No UI to check how much data in source and sync in destination

ETL mainly

Very good interface and easy to understand

many integration to different tools

The calculation of events consumed is not really clear to me

Low-code solution and Hevo manages changes in the APIs of different tools

So we don't need deep expert knowledge to manage our ETL processes.

Working with Hevo has been surprising in several aspects. In addition to being a great tool, they have a team completely focused on problem solving, available when the customer has something to solve and which helps in dealing with problems even before we identify them.

There are some UI details that can be improved, such as searching and viewing the pipe state by schema when there are multiple schemas in the same pipeline.

Hevo is used to allow us to extract data from our multiple data instances, each of which can contain up to thousands of different schemas in a simple and effective way.

Hevo Data makes it easy to connect to many data sources and build a BI-ready data warehouse.

The platform is very stable and the support is quick and helpful.

When using the Models feature in Google BigQuery, the Hevo-created tables have a default expiration date, which, when reached, clears out the data from the table. This cleared out a client's BI solution one time and, while it was not a difficult fix (restoring the tables within BigQuery) it was not ideal.

I build business intelligence solutions and I use Hevo for the most complicated data extraction and warehousing tasks. Because of the breadth of sources and excellent pipeline and modeling features it is really easy to create a complete data warehouse, especially when mixing old and new technology within the same data pipeline (e.g. fusing realtime data from an API with periodic spreadsheet reporting).

Hevo has helped us to implement all our data pipeline to our data warehouse all in a frindly manner with mostly just clicks. Also, there are a lot of native integrations and rest api set up for those that there arent.

the support team is very prestative our account manager Aafreen has helped us with many doubts

The data spikes that heppen when you are setting and adjusting generates extra usage costs, that are not cheap sometimes. Also the custom plans are not very customizable.Also, as the price is in US dollars for us in brazil it become very costly

ETL for our data warehouse: hevo extract many data sources and load to our amazon redshift so we can use with our data vizualion software. It has also quick integrations between aws products. for example redshift to S3

There are a couple of things I like about Hevo but the things that stand out are their customer support and ease-of-use. I used other data ingestion tools in the past and none were as easy to work with as Hevo. That doens't mean it doesn't allow powerful transformations though - it does. When I get stuck and reach out to support, their response is quick (under 5 minutes) and if the issue has to be escalated, it's done so quickly. The response from the escaltion team is equally as impressive.

Once you creat a connector, it can be tricky figuring out how to edit it. It just takes practice though and once you've done it a few times, it's easier.

We have several projects ongoing so we use a variety of connectors - some built in and some using REST API's. I often use Postman to work with the API initially and once I have it working there, translating it into a Hevo connector is often straighforward. I've had to rely on their support team a few times now and they always get me up-and-running within days (sometimes the same day). That keeps my projects running on schedule which is a great thing!

What impressed me most about Hevo were the easy mappings through the visual interface, the customization of ways to extract data from the source of the pipeline and transform data in the middle of the pipeline (along with a test of how it would look after the transformations).

In addition to cordial support in real time. :)

The limitations I had with Hevo were more related to the use outside the scope of the tool than the application itself.

They could implement a way for the pipeline destination to set the auto-incrementing id without having to make the value explicit through the mapping.

Quickly resolved migration issues with real-time updates. That otherwise would require a long process of development, testing and replication to other environments.