Hevo Reviews

Hevo is extremely user friendly and very seamless. Data pipelines can be set in a matter of a few clicks. Our business users are extremely happy with all the data at their disposal for any analysis that they need to do. Hevo's support is very prompt and always available to answer your queries.

When we had started using Hevo 2 years ago, there were only a few sources available. However, I see more and more new sources getting added every month.

It has suited all our needs.
- The most critical part was reading Oplog from production MongoDB replica.
- Cleaning PII and sensitive data on the fly before loading to DWH
- Wide range of sources and even Webhooks (any arbitrary source)

I might only add Hevo is constantly evolving.
I participate in proposing new useful features from my PoV.

Smooth OpLog/Change Stream based syncing is one of the strongest reasons I stick to this platform.

Transformations UI can be a bit better and more user friendly

Ease of use + workflow. Makes setting up complex extraction flows a breez.

UI is sometimes not as intuitive vs. other tools, but this will probably improve.

Extremely Budget friendly, many connector s and destinations, easy to use and good support

Sometimes, the transformations from the raw connectors can be a bit confusing and it requires heavy understanding of the source. But that's expected.

Hevo offers a fair pricing model with competitive features, along with a seamless data integration experience that complies with many data privacy groups. The ability to transform data using python code, auto map object data, and do this all in a user-friendly interface is wonderful. Hevo also ensures pure privacy with data which is vital when using cloud storage integrations.

There was not much to dislike about the software.

Hevo's interface is simple to use, while powerful at the same time. From our tests so far the pipelines work reliably and performantly, and the transformation tools (offered both in a visual manner or through custom Python code for more advanced workflows) are quite useful.
The customer experience and support provided is great.

I seem to be unable to apply new transformation rules retroactively. That would be an important feature to us as sometimes new fields need to be masked or hidden but were already ingested into the destination.

1) Self serve product with super UX - we were able to start our pipelines by ourselves within a day

2) Detailed documentation for every source / destination with appropriate up-to-date references

3) Was impressed by the overall speed - after submitting a job to queue, it picks up the job almost immediately

4) Transformation supports Python which is great, data can be manipulated by custom scripts

5) Full visibility and control over the entire pipeline

6) Schema mapper is great, auto-mapping works for most of the use cases. Manual mapping is also possible. It shows and asks user to confirm what query it is going to execute at the destination, which is good

7) Workbench available to run queries at the destination, custom data models available to create "views" from destination tables

1) Didn't quite like the limit on number of sources in plans

2) Schema mapper doesn't have an option to change column types at the destination

Previously, we were using Fivetran. With Hevo, we get better features for a fraction of the price.

Honestly, I don't have any complaints. Their support is awesome and any issues that I have had, have been resolved within hours.

The UI/UX experience is very intuitive and easy to use

- Default for ingesting data to destination is 5 minutes
- Missing a few data sources, but it looks like they are counting to build

Ease of use: Hevo's UI is very intuitive and easy to learn. With couple of clicks we can easily build scalable pipelines.
Data Transformations: We can write our transformations in python. Hevo also provides out of the box flattening of complex nested json which is very handy while building Mongo pipelines.
Quick and efficient Support: Hevo Support team are quite reachable and always ready to help us solving critical bugs and errors.

Alerting could be much more precise and intelligent.

The things which I most like about Hevo is the automation level in the product. Hevo will take care of everything from source mapping to destination mapping with just a few clicks. It has many useful features, be it table/column auto-mapping , resizing and basic transformations for complex data sources like Mongo where you want to flatten the nested data.

Alarm feature can be little more intuitive.

The best thing I like about Hevo is the ease of use and the integrations that are avaialble for multiple sources, which makes the ETL seamless.

In Schema Mapper/Overview tab in each pipeline, an option to skip muliple collections at a time using a check box might be a good feature which will be very helpful for us, otherwise its now taking lot of manaul effort to skip them if needed in a pipeline.

Hevo's interface is well designed, so that it is straight-forward to set up many pipelines. Unlike other tools, they do not force us into their own standards, for example for naming tables. The service is reliable and performant, including at scale. The team also consists of nice people who have been very friendly and helpful.

We have no complaints. Hevo's MySQL binlog replication works well for us.

We have 10+ pipelines streaming a few million rows from multiple databases to a warehouse. It's very easy to use and configure. It supports all popular database types as sources and we can put custom transformation logic in the pipelines. Hevo's support engineering team has also been very pro-active and helpful throughout our engagement to date.

I think the documentation could be structured in a format of Source (e.g. MongoDB) to Destination (e.g. BigQuery) with the exact steps required to configure this pipeline. Most users would come to Hevo with this type of requirements and it would aid with discoverability.

Ease of building new pipelines and replay queue

Few features are deprecated in updates (eg. JSON parsing strategies). While this is understandable due to performance optimisations, whenever this happens, dev time increases.

Very simple and intuitive process to set up data pipelines. Customer support is very helpful in times when I get stuck. The existing features work without any hassles.

No major cons this far. Custom alerts would be an interesting feature.

Provides features like Workflows which would help us to create data mart.

Probably create a pricing tier for a small data volume use case like ours.

Allows creation of realtime data pipelines from multiple data sources with an option of pre and post data transformations on the data.

The workbench - It is not intelligent moreover any switch from the workbench results in a code loss. So maintaining code or debugging code can be challenging.

It was really easy to set up both on our Mongo Atlas and Amazon Aurora connections where other services failed.

There's no possibility to schedule a pipeline job based on a specific time of the day, eg: run this job at 01:00 AM every day

Flexibility to customise integrations and extractions.

Not much. Maybe build out more connectors (should happen soon though).

It's very easy to use. It's a very simples and intuitive. Without code i can make a great dashboard in my company.

I don't have any difficult. It's simple to use.

Easy, robust, simple. Solved my source data problems in one step!

UNtil they restructured their model, getting started was expensive but the new pricing model is excellent.