dbt vs. Skyvia

The prerequisite is that you have a supported database/data warehouse and have already found a way to ingest your raw data. Then dbt is very well suited to manage your transformation logic if the people using it are familiar with SQL. If you want to benefit from bringing engineering practices to data, dbt is a great fit. It can bring CI/CD practices, version control, automated testing, documentation generation, etc. It is not so well suited if the people managing the transformation logic do not like to code (in SQL) but prefer graphical user interfaces.

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Skyvia is easy to use and set up automated backups. It was one of several tools that we vetted for this purpose – and had the most favorable pricing and integrations to suit our needs. We wanted to have multiple CRM instances backed up daily and allow non-technical team members to manage this, as well as restore them in times of need. Skyvia has allowed us to do this with ease.

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• dbt supports version control through GIT, this allows teams to collaborate and track the data transformation logic.
• dbt allows us to build data models which helps to break complex transformation logic into simple and smaller logic.
• dbt is completely based on SQL which allows data analyst and data engineers to build the transformation logic.
• dbt can be easily integrated with snowflake.

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• Skyvia is good at scheduled bidirectional data integration to/from multiple sources
• The mapping is done automatically which saves a lot of time
• I like that all connectors are included in the price, so I don't have to pay for using some new ones additionally

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• Field-level lineage (currently at table level)
• Documentation inheritance - if a field is documented the downstream field of the same name could inherit the doc info
• Adding python model support (in beta now)

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• If there's something they can improve could be cheaper prices for LaTam
• They can market their services in a larger scale, globally.
• They can market their services in a larger scale, globally.

Reliable, very simple to use, and a range of subscription tiers to suit different needs.

Cons:

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dbt is very easy to use. Basically if you can write SQL, you will be able to use dbt to get what you need done. Of course more advanced users with more technical skills can do more things.

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Loved using Skyvia for our projects, it saved time, allowed us to reach the desired outcome quickly and was easy to maintain. When we first used it we weren't sure we would be able achieve the outcome desired but during the trial it was quickly obvious we would be able to achieve what we needed for data connection and reporting.

I think guys have a really good support team, and even from different time zones we managed to get worthy support.

Simple to setup and maintain

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I actually don't know what the alternative to dbt is. I'm sure one must exist other than more 'roll your own' options like Apache Airflow, say, bu tin terms of super easy managed/cloud data transforms, dbt really does seem to be THE tool to use. It's $50/month per dev, BUT there's a FREE version for 1 dev seat with no read-only access for anyone else, so you can always start with that and then buy yourself a seat later.

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Compared to similar user-friendly data integration systems like Integrate.io, Stitch, or Azure, Skyvia still wins in the number of connectors and pricing policy. Skyvia is a tool for companies like ours, starving for simple but, at the same time, robust and cost-effective data transfer solutions. It doesn't require additional knowledge for implementation and usage because it's no code. We'd recommend Skyvia as the best solution for non-technical staff.

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• Simplified our BI layer for faster load times
• Increased the quality of data reaching our end users
• Makes complex transformations manageable

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• The core of our business lies in analyzing data from various sources, and while ETL itself is not our primary focus, it is a necessary process to achieve our goals. Thanks to Skyvia, we are able to streamline the ETL process at a reasonable price, allowing us to dedicate our efforts to data analysis without the burden of ETL complexities.

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