Very Pleasing. I set it up once and I don't have to worry about it again.

Simple and effective hassle free table syncing between Cloud VM SQL Server and Snowflake DWH.

Getting Hevo white listed with other vendors such as FTP sites is the first big hurdle. Sometimes I'd like to have it sync a view from my source system but it struggles with this. Instead I make it sync the source tables of the view.

As a product analyst we signed up for a free trial of Hevo and finds the onboarding process to be straightforward. We used the built-in connectors to connect their data sources to Hevo and create a data pipeline that transfers data from their sources to their data warehouse in real-time. I appreciates Hevo's user-friendly dashboard, automated error handling, and ability to customize and monitor data transfer. After a few weeks of using Hevo, we have noticed a significant improvement in our team's ability to consolidate and analyze data, enabling us to generate reports and insights more quickly and accurately, leading to better business decisions.

Simple and Intuitive Interface : Way too easy to use .Seamless Integration with Multiple Sources : Integration with almost every possible tool. Real-time Data Transfer.Automated Error Handling and Also showing where the pipeline is failing and what is the reason behind it.

Data transformation needs to have some helping tutorial . Appending data and taking whole data snapshot should have some toggle.

Their customer support team is great with quick turnaround time.

Easy to setup and no/low code approach is what works for someone just starting with Data engineering.

reliability has been a concern with Hevo with downtimes, bugs, corner cases and missed events. It doesn't seem to work well at scale.

Bar none the best customer support I have ever received at any price level. I would pay 10x the price tag and still feel like we won.

The built in database/system connectors and simple GUI interface made it simple to have running in minutes.

We have had a small learning curve bringing query models into Hevo. Nothing crazy and we Hevo support (chat engineers) has almost instantaneous response times.

Hevo Data saved our company in more ways than one. For the bi-directional Hubspot features alone, this tool is worth the cost for us, hands-down. We were able to pull all of our Hubspot data into our data warehouse, annotate, and push back to custom properties and objects. The tool worked so well, we began using it as the core ETL connector for our data lake, and are testing as our scheduled task manager for the core transformations for our data warehouse. The pricing model has worked out well for us. The free trial to prototype how the thing works, and how we could be efficient with our usage of connectors, has also been wonderful.

THe list of connectors is really good, but not 100% where we wish. In addition, migrations from one tool to another (e.g. Intercom -> Hubspot) require us to do a bunch of manual mapping that is hard; other tools have these mappings canned and are therefore easier to use for that use-case.

Hevo was the ideal tool that I needed to bootstrap our data infrastructure. As the person who set everything up I am very satisfied with them and hope that this will be a long partnership.

Hevo is very easy to set up (the whole process is self explanatory) and has a lot of integrations. It also allows for a lot of flexibility with Rest API and Webhook integrations. The UI is very well tought out and the whole product feels professional. I should also point out the Consumer Service, which is great and very helpfull. I get answers every time I talk to them, and I feel my problems are being taken seriously.

Hevo doesn't allow precise control of the Ingestion and Loading frequency and times. You can only choose a frequency or specify certain times, but even this one is limited to a certain number of runs. This is our only limitation with Hevo right now.

Absolutely great. In terms of service itself, reliability, customer support.

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.

If I could give their customer service / support team 10 stars, I would. They've been very responsive and patient while I ask pesky questions.

I really like how intuitive it is to build a new pipeline and get data flowing from an API into a destination database - in our case Azure SQL.

I don't like that REST API calls that yield the same data are not considered "historical" from a billable event standpoint.

Overall the experience has been quite smooth so far. The support provided was great and the initial setup was simple.

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.

Great experience with a very efficient support team.

The tool is quite intuitive to set-up and easy to set up.

Some detailed configuration may sometimes be hard to find in the platform itself.

easy interface for non-data engineers to build and maintain data pipelines.

the cost has increased steeply in the last 1 year to 3.5x.

Its an awesome product. Really very good one to get started with very little friction.

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.

We are using hevo to get Data seamlessly from our transactional DB to our datawarehouse. Hevo is reliable and plays an important part in our data pipelines.

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.

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.

Overall good, from meeting to implementation. The Admin interface is very well built.

We decided to shop around for a new solution because our current provider decided to raise their prices significantly. Hevodata checked all the boxes.

When we first started out, our BigQuery costs went up, but we were able to mitigate that by changing the frequency.

hevo is good data tools

about tools to get asana data using pipeline

this software is so powerfull and easy to operating

It was very easy to sign up and set up Facebook to BigQuery. The user UI is easy to use and step-by-step instructions are included. You don't need a dev to get things moving as long as you're passingly familiar with Facebook and BigQuery and can read directions.

I used Hevo to pipeline data from Facebook into Big Query. The service worked as expected and properly transferred my data. It was one of several services I evaluated for our data pipeline needs.

I had some integration needs that HEVO did not include, so I had to go with another provider who included those. Otherwise, HEVO was amongst my top choices.

Very good. It often fixes problems on it's own without intervention, and is very consistent.

Simple interface. Fast customer service.

Auto mapping sometime acts up, but customer service is very helpful and fixes it.

Ease of use, simple integration, simple transformation

facing issues with deleted or changed entries(events) in the production database, as hevo_marked_delted is not getting updated for all entries and need to connect with cx care for this. For transform only having python 2.8, It should be of the latest version

No coding is the best and all file formats are available to integrate

There is no custom email notification. I receive ETL summary everyday for all the pipelines.

Hevo has been exceptional for us to scale our data warehouse from 0-1. We have barely faced issues with hevo and whenever we have, hevo support has always quickly helped us solve issues. Onboarding new pipelines is very easy to do and negligible dev effort is required.

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.

almost very very good

easy to use and integrate technologies, monitoring tool

I couldn't found an option to make reverse engineering

Awesome product for my simple needs. Great customer service.

Hevo allowed me to set up an ETL without having a coding (python) skillset. I was able to connect spreadsheets to my DB preventing me inputting by hand or contracting out the ETL development. Customer service was awesome!

I imagine I might find some cons as I continue to use the software, but I don't really have any yet. May more options for data types in the destinations???

My overall experience with Hevo is very good. The support team is available anytime and are very quick with their response.

The Hevo is the one frame platform which provides complete cloud ETL features. The data integration from source to destination is very quick. The dashboard provides all the information regarding the history of migration.

The data loading speed might have been much more quicker.