Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Bitwise ETL Converter
Score 7.0 out of 10
N/A
The Bitwise ETL Converter supports data integration standardization and automates ETL migration from disparate systems.N/A
dbt
Score 9.1 out of 10
N/A
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.N/A
Fivetran
Score 8.4 out of 10
N/A
Fivetran replicates applications, databases, events and files into a high-performance data warehouse, after a five minute setup. The vendor says their standardized cloud pipelines are fully managed and zero-maintenance. The vendor says Fivetran began with a realization: For modern companies using cloud-based software and storage, traditional ETL tools badly underperformed, and the complicated configurations they required often led to project failures. To streamline and accelerate…
$0.01
per credit
Pricing
Bitwise ETL ConverterdbtFivetran
Editions & Modules
No answers on this topic
No answers on this topic
Starter
$0.01
per credit
Standard
$0.01
per credit
Enterprise
$0.01
per credit
Offerings
Pricing Offerings
Bitwise ETL ConverterdbtFivetran
Free Trial
NoYesYes
Free/Freemium Version
NoYesNo
Premium Consulting/Integration Services
NoNoNo
Entry-level Setup FeeNo setup feeNo setup feeOptional
Additional Details
More Pricing Information
Community Pulse
Bitwise ETL ConverterdbtFivetran
Considered Multiple Products
Bitwise ETL Converter

No answer on this topic

dbt
Chose dbt
dbt is very flexible and can fit into most data pipelines. This is a pro for most organizations that aren't fully bought into one platform (Google Cloud, etc.)
Chose dbt
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.
Chose dbt
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 …
Chose dbt
Snaplogic is great at the Extraction and Load processes of ETL. It can pull data from anywhere, even behind firewalls. So if you need to get data from various APIs, databases, files, S3, SFTP, etc it is easy to do so. However, it requires special knowledge in order to build …
Chose dbt
I haven't come across anything like DBT before.
Chose dbt
Most ETL pipeline products have a T layer, but dbt just does it better. The transformation is on steroids compared to the others. Also, just allows much more Adhoc solutions for very specific projects. Those ETL tools are probably better on the T part if you don't need too many …
Chose dbt
Airflow can accomplish the same work as dbt (data build tool), however, dbt's (data build tool) development workflow and UI can open up data transformation and modeling work to non-data engineering teams. Looker might also be able to define data models via LookML with a …
Chose dbt
dbt is great because of its transformation capabilities
Fivetran
Chose Fivetran
Matillion requires a lot more initial setup effort and the resulting schemas are also much more "raw" data than the nicely cleaned schemas which Fivetran provides. Therefore it would also require more (manual) post-processing efforts compared to Fivetran. So the savings on time …
Chose Fivetran
Fivetran is much easier to set up and maintain. Airbyte still had a degree of technical knowledge requirement that we didn't have the resources to commit. Fivetran allowed a non-technical employee to establish pipelines and immediately start using the data without having to …
Chose Fivetran
Fivetran is a powerful data replication tool that supported use cases for organization-wide data platforms.
Chose Fivetran
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.
Chose Fivetran
Fivetran came well with the connectors' availability and updates with the source changes.
We had an idea on data requirements in our case which helped us to work out on cost implication and take a decision for Fivetran as a data provider for our organization.
These were 2 …
Chose Fivetran
Fivetran is more intuitive and easier to use than code-based ETL/ELT tools. The data modelling Fivetran performs makes the data more usable more quickly. Fivetran's dbt support and integration is unique.
Chose Fivetran
Honestly, we haven't done much investigation in a while, it just works 360 days of the year. The other five days there may be a hiccup that will throw us a day off of data, but it gets caught up in the end.
Features
Bitwise ETL ConverterdbtFivetran
Data Transformations
Comparison of Data Transformations features of Product A and Product B
Bitwise ETL Converter
-
Ratings
dbt
9.7
Ratings
18% above category average
Fivetran
7.4
Ratings
9% below category average
Simple transformations00 Ratings10.00 Ratings7.50 Ratings
Complex transformations00 Ratings9.50 Ratings7.30 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
Bitwise ETL Converter
-
Ratings
dbt
9.1
Ratings
15% above category average
Fivetran
6.2
Ratings
23% below category average
Data model creation00 Ratings9.70 Ratings2.00 Ratings
Metadata management00 Ratings8.70 Ratings4.00 Ratings
Business rules and workflow00 Ratings9.00 Ratings8.00 Ratings
Collaboration00 Ratings10.00 Ratings7.80 Ratings
Testing and debugging00 Ratings8.00 Ratings9.00 Ratings
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
Bitwise ETL Converter
-
Ratings
dbt
-
Ratings
Fivetran
10.0
Ratings
19% above category average
Connect to traditional data sources00 Ratings00 Ratings10.00 Ratings
Connecto to Big Data and NoSQL00 Ratings00 Ratings10.00 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
Bitwise ETL Converter
-
Ratings
dbt
-
Ratings
Fivetran
8.3
Ratings
3% above category average
Integration with data quality tools00 Ratings00 Ratings8.30 Ratings
Integration with MDM tools00 Ratings00 Ratings8.30 Ratings
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User Ratings
Bitwise ETL ConverterdbtFivetran
Likelihood to Recommend
-
(0 ratings)
10.0
(0 ratings)
8.2
(0 ratings)
Usability
-
(0 ratings)
9.7
(0 ratings)
9.0
(0 ratings)
Performance
-
(0 ratings)
-
(0 ratings)
8.0
(0 ratings)
User Testimonials
Bitwise ETL ConverterdbtFivetran
Likelihood to Recommend
No answers on this topic
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.
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[Fivetran is] very well suited when you are using popular and common data sources, such as the major ad platforms, and SaaS platforms such as Salesforce. If the majority of your data sources are custom internal applications or databases, may be less value as you aren't leveraging the delivered connectors.
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Pros
No answers on this topic
  • user experience makes it easy to work with SQL and version control
  • customer success team and the dbt (data build tool) community help establish best practices
  • thorough and clear documentation
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  • Simplified ETL from a wide range of data sources
  • Stable and painless data pipeline
  • Granular control over what parts of the data source are loaded
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Cons
No answers on this topic
  • 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
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  • Doesn't include support for a Kinesis stream as a data source so couldn't be used for some use cases under consideration
  • Doesn't support the use of "BEFORE DELETE" triggers
  • No support for serverless Aurora
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Usability
No answers on this topic
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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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.
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Performance
No answers on this topic
No answers on this topic
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.
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Alternatives Considered
No answers on this topic
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.
Read full review
Fivetran came well with the connectors' availability and updates with the source changes. We had an idea on data requirements in our case which helped us to work out on cost implication and take a decision for Fivetran as a data provider for our organization. These were 2 places where Fivetran out-performed, other vendors.
Read full review
Return on Investment
No answers on this topic
  • In 3 months we re-wrote the data warehouse (15-20 sources) in dbt with 3 developers.
  • We are using it continually for the past year with no issues.
  • Sorry, I don't have ROI numbers but the impact was huge.
Read full review
  • Saved a lot of manual development days (unable to quantify)
  • Accelerated the time to add a new source to the data warehouse a lot
Read full review
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