dbt Reviews

dbt

5.0 out of 5 stars

Average Ratings 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

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Average Ratings 4 Ratings

Total 5 out of 5 stars
ease 5 out of 5 stars
features 5 out of 5 stars
design 5 out of 5 stars
support 4.5 out of 5 stars

Description

IBM® StreamSets allows users to create and maintain smart streaming data pipelines using an intuitive graphical user interface. This facilitates seamless data integration in hybrid and multicloud environments. IBM StreamSets is used by leading global companies to support millions data pipelines, for modern analytics and intelligent applications. Reduce data staleness, and enable real-time information at scale. Handle millions of records across thousands of pipelines in seconds. Drag-and-drop processors that automatically detect and adapt to data drift will protect your data pipelines against unexpected changes and shifts. Create streaming pipelines for ingesting structured, semistructured, or unstructured data to deliver it to multiple destinations.

Description

dbt Labs is redefining how data teams work with SQL. Instead of waiting on complex ETL processes, dbt lets data analysts and data engineers build production-ready transformations directly in the warehouse, using code, version control, and CI/CD. This community-driven approach puts power back in the hands of practitioners while maintaining governance and scalability for enterprise use. With a rapidly growing open-source community and an enterprise-grade cloud platform, dbt is at the heart of the modern data stack. It’s the go-to solution for teams who want faster analytics, higher quality data, and the confidence that comes from transparent, testable transformations.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Amazon Redshift Yes 
Snowflake Yes 
AccessOwl No 
Azure Industrial IoT Yes 
Couchbase Yes 
DataHub No 
DataOps.live No 
Datakin No 
Elementary No 
Grouparoo No 
HPE Ezmeral Data Fabric Yes 
LocalStack No 
Matia No 
Mode No 
MySQL Yes 
Redis Yes 
SAP HANA Yes 
Secoda No 
Select Star No 
Sifflet No 

Integrations

Amazon Redshift Yes 
Snowflake Yes 
AccessOwl Yes 
Azure Industrial IoT No 
Couchbase No 
DataHub Yes 
DataOps.live Yes 
Datakin Yes 
Elementary Yes 
Grouparoo Yes 
HPE Ezmeral Data Fabric No 
LocalStack Yes 
Matia Yes 
Mode Yes 
MySQL No 
Redis No 
SAP HANA No 
Secoda Yes 
Select Star Yes 
Sifflet Yes 

Pricing Details

$1000 per month
5 active jobs
5 users
50 published pipelines
99.9% uptime
Email Support (Business hours M-F)
Free Trial Yes 
Free Version Yes 

Pricing Details

$100 per user/ month
Free Trial Yes 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) Yes 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Vendor Details

Company Name

IBM

Founded

1911

Country

United States

Website

www.ibm.com/products/streamsets

Vendor Details

Company Name

dbt Labs

Founded

2016

Country

United States

Website

www.getdbt.com

Product Features

DevOps

Approval Workflow Yes 
Dashboard Yes 
KPIs Yes 
Policy Management Yes 
Portfolio Management Yes 
Prioritization Yes 
Release Management Yes 
Timeline Management Yes 
Troubleshooting Reports Yes 

Streaming Analytics

Data Enrichment Yes 
Data Wrangling / Data Prep Yes 
Multiple Data Source Support Yes 
Process Automation Yes 
Real-time Analysis / Reporting Yes 
Visualization Dashboards Yes 

Product Features

Big Data

Collaboration Yes 
Data Blends No 
Data Cleansing Yes 
Data Mining No 
Data Visualization No 
Data Warehousing No 
High Volume Processing No 
No-Code Sandbox No 
Predictive Analytics No 
Templates No 

Data Lineage

Database Change Impact Analysis Yes 
Filter Lineage Links Yes 
Implicit Connection Discovery No 
Lineage Object Filtering No 
Object Lineage Tracing No 
Point-in-Time Visibility No 
User/Client/Target Connection Visibility No 
Visual & Text Lineage View No 

Data Preparation

Collaboration Tools Yes 
Data Access No 
Data Blending Yes 
Data Cleansing Yes 
Data Governance No 
Data Mashup No 
Data Modeling No 
Data Transformation No 
Machine Learning No 
Visual User Interface No 

Data Quality

Address Validation No 
Data Deduplication No 
Data Discovery No 
Data Profililng No 
Master Data Management No 
Match & Merge No 
Metadata Management No 

ETL

Data Analysis No 
Data Filtering Yes 
Data Quality Control Yes 
Job Scheduling No 
Match & Merge No 
Metadata Management No 
Non-Relational Transformations No 
Version Control No 

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