Hevo Data Pipelines
Hevo DataReviews from AWS customer
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Excellent and attentive customer support
What do you like best about the product?
The pipeline setup made sending our data to the warehouse a breeze, and the online support was attentive and addressed a problem with a lagging replication source quickly and efficiently.
What do you dislike about the product?
I would love to see more data sources available out of the box. It would be great if Hevo was our one stop shop for synchronizing the warehouse for all our stores.
What problems is the product solving and how is that benefiting you?
Hevo Data makes the challenging task of synchronizing our data easy and worry-free. With just a few clicks and some straightforward configuration, the spice was quickly flowing.
Best fit to transform your OLTP data to OLAP for small & medium organisations
What do you like best about the product?
It allows you to build a pipeline, transform your data (OLTP to OLAP) and you can store it back to Postgres or my SQL without spending a lot of money on data warehouses until you have petabytes of data.
What do you dislike about the product?
Nothing as such major, the payment auto-debit from credit card won’t work for some time and we do get pending payment alert. In this case, we have to manually reinitiate the payment, Fixing this will make life easier for the users.
What problems is the product solving and how is that benefiting you?
Transformerming my OLTP data to OLAP without building custom data pipelines or not speeding too much on data warehouses as my data volume is very less but has a lot of complex calculations.
This tool allows us to store back the transformed data models' data Postgres SQL that I failed to find in many ETL tools.
This tool allows us to store back the transformed data models' data Postgres SQL that I failed to find in many ETL tools.
Flexibility, simplicity & versatility all in one
What do you like best about the product?
Hevo has immediately become an indispensable part of our technology stack and shortened our development timelines significantly. The most powerful feature in all honestly is the REST connector. The elegance of their solution coupled with a built-in Python module to transform data at run time is truly extraordinary. We've not only integrated dozens of data sources, but the process is so easy to replicate our business users can take advantage of its power.
What do you dislike about the product?
It can be hard to know how many objects you bring in on the first load. We've blown through our quota several times trying to get the data in from a new source into our DB. The default sync period is 15 minutes & when you have millions of objects... that adds up quickly! I also think the object explorer could use some improvement to show the nested JSON better visually - e.g., I still find it easier to use Postman to validate and visualise how a new object is structured.
What problems is the product solving and how is that benefiting you?
The ease of our new ETL process has allowed us to expand the range of SaaS platforms that we work with, as there's no development time required to use the data they create. The result is a more efficient technology team focused on solving customer problems, not debugging some obscure bud in an ETL script.
Painless, fast, easy data migration - but with a ceiling
What do you like best about the product?
Hevo is so simple and easy to hook up with a source data platform and a destination data platform. It really helped us out of a jam in figuring out our data warehouse strategy and implementation. We were recommended to Hevo by Snowflake and it was painless and effortless to get things moving.
I also like that it supports a wide variety of options for handling incremental data, such as change tracking (CT) in SQL Server - I've not found many other products that do. Many support change data capture (CDC) which Hevo does too, but CT is more lightweight and is a good SQL Server option. Hevo supports it but few others do.
I also like that it supports a wide variety of options for handling incremental data, such as change tracking (CT) in SQL Server - I've not found many other products that do. Many support change data capture (CDC) which Hevo does too, but CT is more lightweight and is a good SQL Server option. Hevo supports it but few others do.
What do you dislike about the product?
It would be nice if we could file pipelines under folders or categorise them in some way. It would also be great if we could duplicate pipelines. Let's say we have a bunch of source databases with the same schema and we want to do the same thing to all of them, with a different table prefix when they land in the destination. It would be awesome if we could manage pipelines at scale like this.
However, the biggest thing I dislike is, sadly, Hevo has a limit. It won't stop you mass-creating pipelines but there are only so many it can handle before it can't keep up with schedules.
However, the biggest thing I dislike is, sadly, Hevo has a limit. It won't stop you mass-creating pipelines but there are only so many it can handle before it can't keep up with schedules.
What problems is the product solving and how is that benefiting you?
We use Hevo Data to transfer data from our transactional platforms into a single, consolidated data warehouse. It helped us by being platform-agnostic and giving us one place to manage all our data loads, and more importantly because it's super easy to work with. Support has also been very responsive to our questions.
Recommendations to others considering the product:
Hevo has a simple user interface, but the support is awesome and the pricing is very competitive.
Speed up building your pipes and spend more time on Analytics
What do you like best about the product?
Reduces the effort to manage pipelines from multiple data sources.
Not having to maintain the techniques and knowledge to import data from different sources.
Reduces the skillset constraints in building data teams.
Not having to maintain the techniques and knowledge to import data from different sources.
Reduces the skillset constraints in building data teams.
What do you dislike about the product?
Being able to set custom alerts in monitoring usage (hopefully on the product roadmap).
What problems is the product solving and how is that benefiting you?
Integrating data sources into the Data Lake
Handling of nested data
What do you like best about the product?
It is great how HEVO handles a high level of nesting data, and it is then easy to run query over these table.
What do you dislike about the product?
Google reference sheet doesn't update in real-time.
What problems is the product solving and how is that benefiting you?
Real-time data access. Building models which can be used directly in the dashboards.
Easy to Use
What do you like best about the product?
Easy Data Integration and Easy Data Loading with transformation. Tech Support is very good.
What do you dislike about the product?
It's challenging to identify that which events get loaded. Everytime need to connect with the support team.
What problems is the product solving and how is that benefiting you?
The data pipelines from a lot of different data sources and create a Data-Lake to use the data for all our stakeholders.
The best solution to centralize data and get the most out of it.
What do you like best about the product?
Hevo is really easy to set up and to use. Also, once the data pipeline has been created, you don't have to maintain it. The automation takes care of the rest, sending your data from point A to point B. So no time is wasted!
What do you dislike about the product?
Although Hevo offers one of the widest choice of integrations, we would like to see a couple of new integrations added to the solution.
What problems is the product solving and how is that benefiting you?
Before we started using Hevo, our data was not centralized and was spread across our different tools. This was problematic as our data was not integrated and did not allow us to have a 360° view of our users/customers' journeys. Most of the analyses we wanted to make were either manual and time-consuming, or not feasible at all.
We decided to use Hevo to centralize our data, grabbing the data from our different sources, and sending it into our centralized database: BigQuery.
Hevo helped us not only save time, but also get better insights and make better decisions.
We decided to use Hevo to centralize our data, grabbing the data from our different sources, and sending it into our centralized database: BigQuery.
Hevo helped us not only save time, but also get better insights and make better decisions.
Reliable, affordable and simple
What do you like best about the product?
Hevo has the same ease of use and array of sources as Fivetran, but at a fraction of the cost.
Implementing a change data capture feature would take them to the next level, but the existing product is excellent and priced comparably to the far inferior Stitch.
Connectors are easy to set up, and almost all of them use OAuth2 to authenticate, rather than having to give the data team admin access to every marketing tool so that they can generate API tokens etc (cf. Airbyte).
Overall, you're not going to find a cheaper tool that saves more time than this. You even get an interface to build custom connectors if Hevo are missing any, so there won't be any gaps.
Implementing a change data capture feature would take them to the next level, but the existing product is excellent and priced comparably to the far inferior Stitch.
Connectors are easy to set up, and almost all of them use OAuth2 to authenticate, rather than having to give the data team admin access to every marketing tool so that they can generate API tokens etc (cf. Airbyte).
Overall, you're not going to find a cheaper tool that saves more time than this. You even get an interface to build custom connectors if Hevo are missing any, so there won't be any gaps.
What do you dislike about the product?
There are a few minor gripes with Hevo, but these don't detract from the product:
1. Rather than pricing on rows, the pricing is based on 'events', which include any updates to rows after their initial insert. This makes volume a lot harder to predict, and can lead to some nasty surprises if tables get updated regularly. However, Hevo are happy to give out free events if an unexpected glut of events happens, and historical loads are all free.
2. Destinations aren't very configurable. Usually, ETL tools are used to load data from a variety of sources into a single database, and ideally you'd put each source (e.g. AppsFlyer, Facebook Ads, Postgres RDS) in its own schema. In Hevo, each destination uses only one schema, so the only way you can do this is by configuring a new destination for each schema, copy-pasting the same DB credentials into the UI over and over again. This doesn't take that long, but is an unnecessary initial overhead.
3. There are a few sources we'd like to see that aren't currently represented: Snapchat, Pinterest, Chargebee. These integrations will hopefully come about soon, and in the meantime, Hevo provides an interface for setting up custom API connectors, so there are other ways of proceeding.
1. Rather than pricing on rows, the pricing is based on 'events', which include any updates to rows after their initial insert. This makes volume a lot harder to predict, and can lead to some nasty surprises if tables get updated regularly. However, Hevo are happy to give out free events if an unexpected glut of events happens, and historical loads are all free.
2. Destinations aren't very configurable. Usually, ETL tools are used to load data from a variety of sources into a single database, and ideally you'd put each source (e.g. AppsFlyer, Facebook Ads, Postgres RDS) in its own schema. In Hevo, each destination uses only one schema, so the only way you can do this is by configuring a new destination for each schema, copy-pasting the same DB credentials into the UI over and over again. This doesn't take that long, but is an unnecessary initial overhead.
3. There are a few sources we'd like to see that aren't currently represented: Snapchat, Pinterest, Chargebee. These integrations will hopefully come about soon, and in the meantime, Hevo provides an interface for setting up custom API connectors, so there are other ways of proceeding.
What problems is the product solving and how is that benefiting you?
We're migrating data from our application database into Redshift, as well as unifying all of our marketing data there via the connectors Hevo offers. We've been able to automate many marketing processes via Hevo.
Very simple to replicate, transform and load data from/into multiple sources/destinations
What do you like best about the product?
- The simplicity of the product
- The multiple sources/destinations to work from
- The ability to use SQL to transform data
- The free trial which allows me to stress-test the product
- The multiple sources/destinations to work from
- The ability to use SQL to transform data
- The free trial which allows me to stress-test the product
What do you dislike about the product?
Small improvement area, I would like to load data from a single source into a Bigquery dataset and then use that dataset to model a second set of tables to load in a different BQ dataset. From what I've seen it seems only possible to use models into the same dataset.
What problems is the product solving and how is that benefiting you?
I'm replicating my primary database into a warehouse accessible from teams, and I'm also doing first-off transformations to accelerate the work of our analytics teams.
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