dbt is an SQL development environment, developed by Fishtown Analytics, now known as dbt Labs. The vendor states that with dbt, analysts take ownership of the entire analytics engineering workflow, from writing data transformation code to deployment and documentation. dbt Core is distributed under the Apache 2.0 license, and paid Teams and Enterprise editions are available.
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SSIS
Score 6.5 out of 10
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Microsoft's SQL Server Integration Services (SSIS) is a data integration solution.
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Pricing
dbt
SQL Server Integration Services
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
dbt
SSIS
Free Trial
Yes
No
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
dbt
SQL Server Integration Services
Features
dbt
SQL Server Integration Services
Data Transformations
Comparison of Data Transformations features of Product A and Product B
dbt
9.5
Ratings
15% above category average
SQL Server Integration Services
8.1
Ratings
1% below category average
Simple transformations
10.00 Ratings
8.50 Ratings
Complex transformations
9.00 Ratings
7.70 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
dbt
9.0
Ratings
12% above category average
SQL Server Integration Services
7.4
Ratings
7% below category average
Data model creation
9.50 Ratings
8.60 Ratings
Metadata management
8.50 Ratings
7.10 Ratings
Business rules and workflow
9.00 Ratings
8.20 Ratings
Collaboration
10.00 Ratings
7.30 Ratings
Testing and debugging
8.00 Ratings
6.10 Ratings
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
dbt
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Ratings
SQL Server Integration Services
7.5
Ratings
11% below category average
Connect to traditional data sources
00 Ratings
8.80 Ratings
Connecto to Big Data and NoSQL
00 Ratings
6.20 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
dbt (Data Build Tool) is best suited for doing the data transformation. dbt is just a transformation tool and it is not suitable for building a data pipeline which requires extraction of data and loading. dbt is well suited for SQL based transformation logic and it is less appropriate when transformation logic requires python.
Ideal for daily standard ETL use cases whether the data is sourced from / transferred to the native connectors (like SQL Server) or FTP. Best if the company uses MS suite of tools. There are better options in the market for chaining tasks where you want a custom flow of executions depending on the outcome of each process or if you want advanced functionality like API connections, etc.
Slow load times of the dbt cloud environment (they're working on it via a new UI though)
More out-of-the-box solutions for managing procedures, functions, etc would be nice to have, but honestly, it's pretty easy to figure out how to adapt dbt macros
SSIS is responsible for running core business processed managing core business data. It can be managed, improved and expanded using minimal internal resources. It is also able to support all of our current data infrastructure. Replacing SSIS would be time consuming and costly with no apparent ROI.
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.
SSIS has a drag and drop based developer interface, so it is relatively straight forward to get started. You can start to get into the weeds pretty quickly as your solution becomes more complex. However, most of the base functions are right in front of you for a developer. You can also set project and solution level parameters, so when you deploy to new environments, you don't have to jump into each package to change your variables and settings. (For example, default directory to ingest flat files).
Raw performance is great. At times, depending on the machine you are using for development, the IDE can have issues. Deploying projects is very easy and the tool set they give you to monitor jobs out of the box is decent. If you do very much with it you will have to write into your projects performance tracking though.
The support, when necessary, is excellent. But beyond that, it is very rarely necessary because the user community is so large, vibrant and knowledgable, a simple Google query or forum question can answer almost everything you want to know. You can also get prewritten script tasks with a variety of functionality that saves a lot of time.
The implementation may be different in each case, it is important to properly analyze all the existing infrastructure to understand the kind of work needed, the type of software used and the compatibility between these, the features that you want to exploit, to understand what is possible and which ones require integration with third-party tools
Matillion is graphical versus dbt, which is SQL code-based (that, of course, is a matter of personal preference and not an objective advantage). The integrated testing, documentation generation, lineage, etc., were additional criteria that led us to choose dbt.
I think SQL Server Integration Services is better suited for on-premises data movement and ADF is more suited for the cloud. Though ADF has more connectors, SQL Server Integration Services is more robust and has better functionality just because it has been around much longer
Without this, we would have to manually update a spreadsheet of our SQL Server inventory
We would also have poor alerting; if an instance was down we wouldn't know until it was reported by a user
We only have one other person who uses SQL Server Integration Services , he's the expert. It would fall to me without him and I would not enjoy being responsible for it.
