eponkratova/dbt.csv

## dbt.csv

          
            tool
            tool category
            link
            integration
            dbt Cloud/dbt Core (use with caution)

            
              Sisu
              AI/ML
              https://sisudata.com/
              ...you can define your metrics in dbt and then use them in Sisu for one-click analyses.
              dbt Cloud

            
              Continual
              AI/ML
              https://continual.ai/
              Continual integrates with dbt by allowing dbt users to define entities, feature sets, and predictive models directly from their existing dbt models.
              dbt Cloud

            
              Holistics 
              BI
              https://www.holistics.io/
              Holistics fully integrates with your dbt project, allows you to perform data modeling and transformation at dbt layer, and push those definitions to Holistics BI layer
              dbt Cloud/dbt Core

            
              mode
              BI
              https://mode.com/
              Mode customers can now get better views on data freshness with our dbt integration.
              dbt Cloud

            
              thoughtspot
              BI
              https://www.thoughtspot.com/
              ThoughtSpot’s dbt integration allows you to easily provide your existing dbt models and automatically create ThoughtSpot Worksheets, which you can use to search your data.
              dbt Cloud

            
              Transform
              BI
              https://transform.co/
               Transform then surfaces useful metadata from your dbt models—like the time of the last successful run—and links to model documentation directly in the Transform user interface (UI).
              ?

            
              Sigma
              BI
              https://www.sigmacomputing.com/
              Access the docs & metadata generated from dbt jobs  directly in Sigma.
              dbt Cloud

            
              Lightdash
              BI
              https://www.lightdash.com/
              Lightdash instantly turns your dbt project into a full-stack BI platform. Analysts write metrics and Lightdash enables self-serve for the entire business.
              ?

            
              GoodData
              BI
              https://www.gooddata.com/
              You can define simple metrics in dbt (during transformation/modeling) and derive them in headless BI (GoodData). 
              ?

            
              FlexIt
              BI
              https://flexitanalytics.com/
              FlexIt leverages the lineage feature of dbt to show both upstream model dependencies, as well as downstream dashboards and reports. In addition to lineage paths.
              dbt Cloud/dbt Core

            
              Hex
              BI
              https://hex.tech/
              Hex has two separate integrations with dbt Cloud — the dbt metadata integration, and the dbt server integration.
              dbt Cloud/dbt Core

            
              Houseware
              data platform
              https://www.houseware.io/
              Houseware launches integration with the dbt Semantic Layer to accelerate warehouse-native data apps for an enhanced revenue experience.
              ?

            
              deepnote
              Data science
              https://deepnote.com/
              Using the transformed data. The most common use case is to build Deepnote notebooks based on the tables and views which are the results of the dbt jobs.
              dbt Cloud/dbt Core

            
              validio
              data observability
              https://validio.io/
              All to say, Validio enables data quality validation to be applied to a much broader set of business critical data sources than dbt tests allow.
              ?

            
              soda
              data observability
              https://www.soda.io/
              Integrate Soda with dbt to access dbt test results from within your Soda Cloud account
              dbt Cloud/dbt Core

            
              re_data 
              data observability
              https://www.getre.io/
              Currently, re_data focuses on observing the dbt project (together with underlaying data warehouse - Postgres, BigQuery, Snowflake, Redshift).
              dbt Core

            
              Elementary 
              data observability
              https://www.elementary-data.com/
              Elementary dbt tests collect metrics and metadata over time, such as freshness, volume, schema changes, distribution, cardinality, etc
              ?

            
              bigeye
              data observability
              https://www.bigeye.com/
              Automatically quarantining bad data with Bigeye and dbt
              dbt Cloud

            
              montecarlodata
              data observability
              https://www.montecarlodata.com/
              Monte Carlo’s integration with dbt Core, helping teams ship more reliable data, faster, through robust testing and monitoring. 
              dbt Cloud/dbt Core

            
              kensu
              data observability
              https://www.kensu.io/
              Kensu developed a brand new dbt integration that helps engineering teams control data transformations performed by dbt and test data in production.
              ?

            
              Metaplane
              data observability
              https://www.metaplane.dev
              Metaplane can access your dbt cloud metadata to extract metadata about job runs metadata such as run durations, models generated by dbt, and lineage relationships between models. Metaplane is able to match tables in your warehouse with dbt models to determine the causality and consequences of table failure.
              dbt Cloud

            
              Databand
              data observability
              https://databand.ai/
              You can use Databand's dbt monitor to track dbt jobs by directly monitoring your dbt Cloud environemnt. 
              dbt Cloud

            
              Anomalo
              data quality
              https://www.anomalo.com/
              Anomalo's data quality monitoring solution automatically detects data issues related to dbt metrics and allows data teams to understand their root causes.
              ?

            
              workstream
              data platform
              https://www.workstream.io/
              Workstream integrates with dbt projects to automatically sync exposures and shows real-time monitoring of data quality and freshness.
              dbt Cloud

            
              Rakam 
              data platform
              https://rakam.io/
              rakam connects to your dbt core project. You can transform and document your data with dbt and define your metrics as code with our data modeling tool, Metriql.
              dbt Core

            
              keboola
              dataops
              https://www.keboola.com/
              Bring your existing dbt code, start fresh or start by orchestrating existing dbt cloud jobs as a part of bigger data pipelines. Keboola supports remote execution of dbt jobs on your existing DWH as well. Collect job information, including run artifacts. Visualize dbt docs in one click — no need for scripting and custom hosting.
              dbt Cloud/dbt Core

            
              datacoves
              dataops
              https://datacoves.com/
              dbt-coves is a CLI tool that automates certain tasks for dbt, making life simpler for the dbt user.
              ?

            
              prefect
              dataops
              https://www.prefect.io/
               Prefect enables dbt jobs to be part of cross-platform workflow, with advanced scheduling, dependencies, and failure handling.
              dbt Cloud

            
              Astronomer
              dataops
              https://registry.astronomer.io/
              Use Airflow or Astronomer to orchestrate and execute dbt models as DAGs.

            
              Datagalaxy
              metadata
              https://www.datagalaxy.com
              DataGalaxy provides a large set of connectors to effortlessly identify and map your physical data, processings, and usages
              ?

            
              data.world Collector
              metadata
              https://data.world/
              The information cataloged by the collector includes dbt metadata.
              ?

            
              collibra
              metadata
              https://www.collibra.com/us/en
              This integration extracts dbt metadata using GraphQL calls and dbt API calls, then transforms the metadata and loads it to Collibra by Collibra API calls.
              dbt Cloud

            
              zeenea
              metadata
              https://zeenea.com/
              Easily document your DBT data processes with our automated lineage reconstruction feature.
              ?

            
              open-metadata
              metadata
              https://open-metadata.org/
              OpenMetadata integrates metadata from dbt.
              ?

            
              amundsen
              metadata
              https://www.amundsen.io/
              There are several tools to capture data lineage from a data source, such as dbt and OpenLineage.
              dbt Core?

            
              selectstar
              metadata
              https://www.selectstar.com/
              Select Star can integrate with dbt in two ways (Sync dbt documentation, Create separate data source).
              dbt Cloud/dbt Core

            
              secoda
              metadata
              https://secoda.co/
               With the Secoda and dbt integration, teams can finally get simple data discovery for every employee.
              ?

            
              Datakin
              metadata
              https://datakin.com/
              If you use Datakin to observe your dbt models as they run, you can always know exactly where your datasets came from and how they were created.
              ?

            
              datahubproject
              metadata
              https://datahubproject.io/
              The new dbt integration collects model, source, lineage and schema information. Other integrations (such as Airflow or Superset) can add relationships between your dbt datasets and charts, pipelines, or external datasets. Now, you can have a complete picture of how dbt connects to the rest of your data ecosystem, all in one place.
              dbt Cloud/dbt Core

            
              Immuta
              metadata
              https://immuta.com
              ...so that updates run through dbt populate within Immuta as new data sources, column descriptions, data source descriptions, and tags.'
              dbt Cloud

            
              Dagster 
              orchestration
              https://dagster.io/
              Dagster orchestrates dbt alongside other technologies and provides built-in operational and data observability capabilities. 
              dbt Cloud

            
              getcensus
              reverse ETL
              https://www.getcensus.com/
              When using the Census dbt integration, dbt CI Checks will run in your GitHub account and let you know if you’re about to drop, rename, or move a dbt model that a Census sync depends on. 
              dbt Cloud/dbt Core

            
              Hightouch
              reverse ETL
              https://hightouch.com/
              The dbt Cloud extension lets you schedule Hightouch syncs to run as soon as a dbt Cloud job completes.
              dbt Cloud

            
              cube
              semantic
              https://cube.dev/
              Today, we are happy to announce an integration with dbt Metrics. Cube can now read metrics from dbt, merge them into Cube’s data model, provide caching and access control, and expose metrics via our APIs to downstream applications.
              ?

            
              Preset
              semantic
              https://preset.io/
              dbt is a framework for managing data transformation SQL queries in source control and running them inside your database. dbt makes it easy to reliably produce clean datasets and metrics for visualization in Preset.
              dbt Core

            
              datafold
              testing
              https://www.datafold.com/
              Get full test coverage across all your dbt models. See how SQL updates effect tables, columns, rows, and dashboards before merging to production.
              dbt Cloud/dbt Core

            
              PipeRider 
              testing
              https://piperider.io/
              PipeRider is a non-intrusive open-source platform for adding profiling and assertions to data sources (such as dbt, Postgres, Snowflake).
              ?

            
              fivetran
              universal data integration (ELT)
              https://www.fivetran.com/
              Orchestrate custom data transformations in your destination with Transformations for dbt Core
              dbt Core

            
              precog
              universal data integration (ELT)
              https://precog.com/
              Scalable Self-Service data ingest for DBT.
              ?

            
              Airbyte 
              universal data integration (ELT)
              https://airbyte.com/
               Integrate SQL based transformations with Airbyte syncs using specialized transformation tool: dbt.
              dbt Core

            
              meltano
              universal data integration (ELT)
              https://meltano.com/
              The dbt transformer is a plugin for running SQL-based transformations on data stored in your warehouse. 
              ?

            
              matillion
              universal data integration (ELT)
              https://www.matillion.com/
              You will now be able to trigger your existing dbt scripts in a Matillion pipeline without having to write any code or leave your Matillion instance. 
              ?

            
              Striim 
              universal data integration (ELT)
              https://www.striim.com/
              Striim streams real-time data into the target warehouse where analysts can leverage dbt to build models and transformations.
              dbt Cloud

            
               Qlik Application Automation 
              universal data integration (ELT)
              https://www.qlik.com/us/
              Dbt (data build tool) is a solution that enables data analysts and engineers to transform, test, and document data in their cloud data warehouses. Use the connector and blocks to control dbtCloud jobs as an action within Qlik Cloud.  
              ?

            
              Alteryx 
              universal data integration (ELT)
              https://www.alteryx.com/
              Our goal is to provide you with the best of Designer Cloud and dbt Core to uncover, troubleshoot, and address potential data quality issues. 
              dbt Core

## gistfile1.txt
'
tool	tool category	link	integration	dbt Cloud/dbt Core (use with caution)
Sisu	AI/ML	https://sisudata.com/	...you can define your metrics in dbt and then use them in Sisu for one-click analyses.	dbt Cloud
Continual	AI/ML	https://continual.ai/	Continual integrates with dbt by allowing dbt users to define entities, feature sets, and predictive models directly from their existing dbt models.	dbt Cloud
Holistics	BI	https://www.holistics.io/	Holistics fully integrates with your dbt project, allows you to perform data modeling and transformation at dbt layer, and push those definitions to Holistics BI layer	dbt Cloud/dbt Core
mode	BI	https://mode.com/	Mode customers can now get better views on data freshness with our dbt integration.	dbt Cloud
thoughtspot	BI	https://www.thoughtspot.com/	ThoughtSpot’s dbt integration allows you to easily provide your existing dbt models and automatically create ThoughtSpot Worksheets, which you can use to search your data.	dbt Cloud
Transform	BI	https://transform.co/	Transform then surfaces useful metadata from your dbt models—like the time of the last successful run—and links to model documentation directly in the Transform user interface (UI).	?
Sigma	BI	https://www.sigmacomputing.com/	Access the docs & metadata generated from dbt jobs directly in Sigma.	dbt Cloud
Lightdash	BI	https://www.lightdash.com/	Lightdash instantly turns your dbt project into a full-stack BI platform. Analysts write metrics and Lightdash enables self-serve for the entire business.	?
GoodData	BI	https://www.gooddata.com/	You can define simple metrics in dbt (during transformation/modeling) and derive them in headless BI (GoodData).	?
FlexIt	BI	https://flexitanalytics.com/	FlexIt leverages the lineage feature of dbt to show both upstream model dependencies, as well as downstream dashboards and reports. In addition to lineage paths.	dbt Cloud/dbt Core
Hex	BI	https://hex.tech/	Hex has two separate integrations with dbt Cloud — the dbt metadata integration, and the dbt server integration.	dbt Cloud/dbt Core
Houseware	data platform	https://www.houseware.io/	Houseware launches integration with the dbt Semantic Layer to accelerate warehouse-native data apps for an enhanced revenue experience.	?
deepnote	Data science	https://deepnote.com/	Using the transformed data. The most common use case is to build Deepnote notebooks based on the tables and views which are the results of the dbt jobs.	dbt Cloud/dbt Core
validio	data observability	https://validio.io/	All to say, Validio enables data quality validation to be applied to a much broader set of business critical data sources than dbt tests allow.	?
soda	data observability	https://www.soda.io/	Integrate Soda with dbt to access dbt test results from within your Soda Cloud account	dbt Cloud/dbt Core
re_data	data observability	https://www.getre.io/	Currently, re_data focuses on observing the dbt project (together with underlaying data warehouse - Postgres, BigQuery, Snowflake, Redshift).	dbt Core
Elementary	data observability	https://www.elementary-data.com/	Elementary dbt tests collect metrics and metadata over time, such as freshness, volume, schema changes, distribution, cardinality, etc	?
bigeye	data observability	https://www.bigeye.com/	Automatically quarantining bad data with Bigeye and dbt	dbt Cloud
montecarlodata	data observability	https://www.montecarlodata.com/	Monte Carlo’s integration with dbt Core, helping teams ship more reliable data, faster, through robust testing and monitoring.	dbt Cloud/dbt Core
kensu	data observability	https://www.kensu.io/	Kensu developed a brand new dbt integration that helps engineering teams control data transformations performed by dbt and test data in production.	?
Metaplane	data observability	https://www.metaplane.dev	Metaplane can access your dbt cloud metadata to extract metadata about job runs metadata such as run durations, models generated by dbt, and lineage relationships between models. Metaplane is able to match tables in your warehouse with dbt models to determine the causality and consequences of table failure.	dbt Cloud
Databand	data observability	https://databand.ai/	You can use Databand's dbt monitor to track dbt jobs by directly monitoring your dbt Cloud environemnt.	dbt Cloud
Anomalo	data quality	https://www.anomalo.com/	Anomalo's data quality monitoring solution automatically detects data issues related to dbt metrics and allows data teams to understand their root causes.	?
workstream	data platform	https://www.workstream.io/	Workstream integrates with dbt projects to automatically sync exposures and shows real-time monitoring of data quality and freshness.	dbt Cloud
Rakam	data platform	https://rakam.io/	rakam connects to your dbt core project. You can transform and document your data with dbt and define your metrics as code with our data modeling tool, Metriql.	dbt Core
keboola	dataops	https://www.keboola.com/	Bring your existing dbt code, start fresh or start by orchestrating existing dbt cloud jobs as a part of bigger data pipelines. Keboola supports remote execution of dbt jobs on your existing DWH as well. Collect job information, including run artifacts. Visualize dbt docs in one click — no need for scripting and custom hosting.	dbt Cloud/dbt Core
datacoves	dataops	https://datacoves.com/	dbt-coves is a CLI tool that automates certain tasks for dbt, making life simpler for the dbt user.	?
prefect	dataops	https://www.prefect.io/	Prefect enables dbt jobs to be part of cross-platform workflow, with advanced scheduling, dependencies, and failure handling.	dbt Cloud
Astronomer	dataops	https://registry.astronomer.io/	Use Airflow or Astronomer to orchestrate and execute dbt models as DAGs.
Datagalaxy	metadata	https://www.datagalaxy.com	DataGalaxy provides a large set of connectors to effortlessly identify and map your physical data, processings, and usages	?
data.world Collector	metadata	https://data.world/	The information cataloged by the collector includes dbt metadata.	?
collibra	metadata	https://www.collibra.com/us/en	This integration extracts dbt metadata using GraphQL calls and dbt API calls, then transforms the metadata and loads it to Collibra by Collibra API calls.	dbt Cloud
zeenea	metadata	https://zeenea.com/	Easily document your DBT data processes with our automated lineage reconstruction feature.	?
open-metadata	metadata	https://open-metadata.org/	OpenMetadata integrates metadata from dbt.	?
amundsen	metadata	https://www.amundsen.io/	There are several tools to capture data lineage from a data source, such as dbt and OpenLineage.	dbt Core?
selectstar	metadata	https://www.selectstar.com/	Select Star can integrate with dbt in two ways (Sync dbt documentation, Create separate data source).	dbt Cloud/dbt Core
secoda	metadata	https://secoda.co/	With the Secoda and dbt integration, teams can finally get simple data discovery for every employee.	?
Datakin	metadata	https://datakin.com/	If you use Datakin to observe your dbt models as they run, you can always know exactly where your datasets came from and how they were created.	?
datahubproject	metadata	https://datahubproject.io/	The new dbt integration collects model, source, lineage and schema information. Other integrations (such as Airflow or Superset) can add relationships between your dbt datasets and charts, pipelines, or external datasets. Now, you can have a complete picture of how dbt connects to the rest of your data ecosystem, all in one place.	dbt Cloud/dbt Core
Immuta	metadata	https://immuta.com	...so that updates run through dbt populate within Immuta as new data sources, column descriptions, data source descriptions, and tags.'	dbt Cloud
Dagster	orchestration	https://dagster.io/	Dagster orchestrates dbt alongside other technologies and provides built-in operational and data observability capabilities.	dbt Cloud
getcensus	reverse ETL	https://www.getcensus.com/	When using the Census dbt integration, dbt CI Checks will run in your GitHub account and let you know if you’re about to drop, rename, or move a dbt model that a Census sync depends on.	dbt Cloud/dbt Core
Hightouch	reverse ETL	https://hightouch.com/	The dbt Cloud extension lets you schedule Hightouch syncs to run as soon as a dbt Cloud job completes.	dbt Cloud
cube	semantic	https://cube.dev/	Today, we are happy to announce an integration with dbt Metrics. Cube can now read metrics from dbt, merge them into Cube’s data model, provide caching and access control, and expose metrics via our APIs to downstream applications.	?
Preset	semantic	https://preset.io/	dbt is a framework for managing data transformation SQL queries in source control and running them inside your database. dbt makes it easy to reliably produce clean datasets and metrics for visualization in Preset.	dbt Core
datafold	testing	https://www.datafold.com/	Get full test coverage across all your dbt models. See how SQL updates effect tables, columns, rows, and dashboards before merging to production.	dbt Cloud/dbt Core
PipeRider	testing	https://piperider.io/	PipeRider is a non-intrusive open-source platform for adding profiling and assertions to data sources (such as dbt, Postgres, Snowflake).	?
fivetran	universal data integration (ELT)	https://www.fivetran.com/	Orchestrate custom data transformations in your destination with Transformations for dbt Core	dbt Core
precog	universal data integration (ELT)	https://precog.com/	Scalable Self-Service data ingest for DBT.	?
Airbyte	universal data integration (ELT)	https://airbyte.com/	Integrate SQL based transformations with Airbyte syncs using specialized transformation tool: dbt.	dbt Core
meltano	universal data integration (ELT)	https://meltano.com/	The dbt transformer is a plugin for running SQL-based transformations on data stored in your warehouse.	?
matillion	universal data integration (ELT)	https://www.matillion.com/	You will now be able to trigger your existing dbt scripts in a Matillion pipeline without having to write any code or leave your Matillion instance.	?
Striim	universal data integration (ELT)	https://www.striim.com/	Striim streams real-time data into the target warehouse where analysts can leverage dbt to build models and transformations.	dbt Cloud
Qlik Application Automation	universal data integration (ELT)	https://www.qlik.com/us/	Dbt (data build tool) is a solution that enables data analysts and engineers to transform, test, and document data in their cloud data warehouses. Use the connector and blocks to control dbtCloud jobs as an action within Qlik Cloud.	?
Alteryx	universal data integration (ELT)	https://www.alteryx.com/	Our goal is to provide you with the best of Designer Cloud and dbt Core to uncover, troubleshoot, and address potential data quality issues.	dbt Core