Hevo Reviews - Page 4

Great Customer Support in case of problems

It is quite expensive per row so the quality of the support really matters.

User friendly interface Easy to build Pipeline Faster

Sometime Data compatibility issue which CSV for date_time field

Customer Support, ease of integrating new sources.

Can't edit the slack notifications with salutations.

Hevodata has been one of the easiest data pipelines integration that I have used. It’s very easy to get started and setup your pipelines.

The web UI is still a bit buggy and the logs need to be more verbose. It is very difficult to figure out why, if any, issues are there with your data pipeline.

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.

Cross platform migrations are easy! Hevo provides pre-built connectors for a vast array of data sources, including databases, cloud applications, file storage, marketing platforms, and more.

Using a managed service like Hevo can lead to vendor lock-in. If you decide to migrate to a different data integration platform or infrastructure in the future, it may involve additional effort and cost.

i really like the nice and easy UI to setup pipeline, apart from it I really like their schema mapper function also the latest transformation drag and drop UI

I don't like that they don't do data qc or do not provide feature to setup data quality rules like glue and databricks does

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

Constantly running (real time) and the ability to customize mapping

More videos to explain detail how to use the tool

Flexibility to customise integrations and extractions.

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

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.

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

I really liked that its the only product made for non-technical users since its the only one I could install into my systems

So far I think it needs more integrations

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.

Thank you for sharing your review, Jeferson.

Automated history load and scheduling of pipelines and automapping.

pretty cumbersome to select and deselect some of the options in adding tables in the pipeline.

SCHEMA MAPPING - It is a good feature that makes it hassle-free for schema creation

There should be support for using the Standby server as a source for logical replication on PostgreSQL

It is easy to use and affordable, and also has a lot of integration.

team management and customizable permission management aren't that good but that's not too much of a problem

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.

Easy to set up and create multiple pipelines across many different sources

Lot of scope in automation to fix errors in pipeline or unloaded events

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.

Creating ETL pipelines, models and work flows.

Sometimes it seems difficult on changing the import table

Extremely Easy to build pipelines from various data sources. Easy to debug and resync in case of failures.

L2 Documentation for certain data sources seem to be a bit outdated.

Connectors, automapping and ease of use overall.

Missing ELT(Activate deprecation), our use case was something around pushing data into s3 and salesforce.As per my knowledge, hevo used to support s3 as destination via pipelines and salesforce as target via activate. This is no longer supported, it would have been useful if it weren't deprecated.