dbt vs. Fivetran vs. Salesforce Data 360

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.

Incentivized

Fivetran's business model justifies the use-case where we require data from a single source basically a lot of data but if the requirement is not on the heavier side, Fivetran comes to costly operation when compared to its peers. Otherwise, I'll recommend Fivetran for stability and update and seamless service provider.

Incentivized

Great tool for client management, sales tracking, cases studies. Using is as the source of truth for all client communication. Allowing more integration options for cc and ACH payments. Right now the options are limited and only integrate with strict processing capabilities that are not always in the businesses best interest.

Incentivized

• 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.

Incentivized

• Easily connects to source data using delivered connectors
• Transforms data into standard models and schemas
• Has very good documentation to help quickly setup connectors

Incentivized

• Allows use to bring external data into Salesforce as zero-copy
• Is able to present data using standard Salesforce reports familiar to our users
• Allows us to establish multiple relationships between our CRM data and the external data to contextualize the imported data.

Incentivized

• 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)

Incentivized

• Very difficult to get connectors enhanced if a specific needed object is not supported by them
• Depending on the edition needed and the data volumes, can get quite expensive

Incentivized

• pricing or costing visibilty, we can't estimate what would be consumption this month and suddenly we get surprised
• CI/CD can be improved, that looks a difficult and hard
• Also sandbox comes with many limitation so very hard to replicate production like environment to test

Incentivized

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.

Incentivized

Very easy and intuitive to setup and maintain as there usually are not that many options. Very well documented (e.g. how to setup each connector, how the schema looks like, any specific features of this connector etc.). Also the operation is intuitive, e.g. you have status pages, log pages, configuration pages etc. for each connector.

Incentivized

Most of the daily use features, are very usr friendly, intuitive, every end user can learn how to manage and operate basic activities such as enter information, send an email, send a campaign, create an email marketing template, run a report on the renewals for the month, open and close a support case, create new account or a new contact, etc

Incentivized

It runs pretty well and gets our data from point A to point cluster quickly enough. Honestly, it's not something I think about unless it breaks and that's pretty rare.

Incentivized

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.

Incentivized

We never seriously considered using anything else. Our data engineers had used Fivetran extensively in previous roles so when it came time to make a decision, there wasn't much of a process. They gladly signed the contract with Fivetran pretty quickly.

Incentivized

we have evaluated Snowflake, adobe rt-cdp as well. They also offer a very strong capabilities but the Data 360 is more suitable for us because of the same Salesforce ecosystem. The main key factor is without any custom code we were able to include it into our automations. And ofcourse with agentforce already in plans, we had to pick Data 360

Incentivized

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

Incentivized

• It has been very positive in serving BI team with new source requests
• It has been OK at scaling to match as data volumes as source data size grows

Incentivized

• Salesforce Data Cloud has a positive impact on me as a realtor because it is easy to generate reports on customer data and see what is needed to be bumped to the next level. We have to earn a certain commission by the end of the year and it makes it easy to see how close you are
• It has a positive impact on keeping track of customers because it is nice to have it all in one place which is a nice time saver
• I like that you can even see customer info from other agents making it nice to compare and try and pass others
• Makes the customers journey smooth sailing because everything is in one place

Incentivized