dbt
5.0 out of 5 starsSemarchy Data Platform (SDP)
4.7 out of 5 starsRatings and Reviews 4 Ratings
Ratings and Reviews 64 Ratings
What is dbt?
dbt is the leading analytics engineering platform for modern businesses. By combining the simplicity of SQL with the rigor of software development, dbt allows teams to:
- Build, test, and document reliable data pipelines
- Deploy transformations at scale with version control and CI/CD
- Ensure data quality and governance across the business
Trusted by thousands of companies worldwide, dbt Labs enables faster decision-making, reduces risk, and maximizes the value of your cloud data warehouse. If your organization depends on timely, accurate insights, dbt is the foundation for delivering them.
What is Semarchy Data Platform (SDP)?
Semarchy Data Platform (SDP) provides an enterprise data management environment that unifies data integration, master data management, data quality, and governance within a single platform. The solution is built around the concept of reusable Data Products that package business information, processing logic, and access interfaces into independently managed components. Each Data Product can contain data entities, validation rules, transformation pipelines, APIs, semantic models, and descriptive metadata that define how information is structured and consumed. Built-in ownership and lifecycle management capabilities help organizations maintain accountability and consistency as data assets evolve. SDP supports a DataOps-oriented development process in which engineers design solutions using Visual Studio Code, track changes through Git, and manage releases with continuous integration and deployment pipelines. Automated testing and rollback functionality enable teams to validate modifications and recover from unsuccessful deployments without disrupting established data workflows. AI-powered design assistance helps users create data models, configure business rules, and accelerate the development of governed data assets. Integrated governance functionality includes data lineage, access management, quality controls, and metadata management to support trusted information throughout its lifecycle. Organizations can deploy the platform as a managed SaaS solution, within self-hosted infrastructure, or natively in Snowflake, depending on their technical and operational requirements. By replacing fragmented data management tools with a unified, reusable architecture, Semarchy Data Platform helps enterprises reduce integration complexity, accelerate data delivery, and provide consistent information for analytics, applications, and business operations.
Integrations Supported
Azure Marketplace
AccessOwl
Analytify AI
Braight
Databricks
Decube
Flyte
Fraoula Data Auditor
Google Cloud BigQuery
Integrations Supported
Azure Marketplace
Amazon Web Services (AWS)
API Availability
API Availability
Pricing Information
$100 per user/ month
Free Version
Free Trial Offered?
Pricing Information
Pricing not provided
Supported Platforms
SaaS
Supported Platforms
SaaS
Windows
Mac
On-Prem
Linux
Customer Service / Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
dbt Labs
Date Founded
2016
Company Location
United States
Company Website
www.getdbt.com
Company Facts
Organization Name
Semarchy
Date Founded
2011
Company Location
United States
Company Website
www.semarchy.com
Categories and Features
Big Data
Collaboration
Data Cleansing
Data Catalog
Not specified
Data Engineering
Not specified
Data Integration
Not specified
Data Lineage
Database Change Impact Analysis
Filter Lineage Links
Data Modeling
Not specified
Data Pipeline
Not specified
Data Preparation
Collaboration Tools
Data Blending
Data Cleansing
Data Quality
Not specified
DataOps
Not specified
ETL
Data Filtering
Data Quality Control
Semantic Layer
Not specified
Categories and Features
Data Discovery
Contextual Search
Data Classification
Data Matching
False Positives Reduction
Self Service Data Preparation
Sensitive Data Identification
Visual Analytics
Data Governance
Access Control
Data Discovery
Data Mapping
Data Profiling
Deletion Management
Email Management
Policy Management
Process Management
Roles Management
Storage Management
Data Management
Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge
Data Quality
Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management
ETL
Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control
Integration
Dashboard
ETL - Extract / Transform / Load
Metadata Management
Multiple Data Sources
Web Services
Master Data Management
Data Governance
Data Masking
Data Source Integrations
Hierarchy Management
Match & Merge
Metadata Management
Multi-Domain
Process Management
Relationship Mapping
Visualization
Product Data Management
Bill of Material Management
Document Management
Formula Management
Product Analytics
Product Lifecycle Management
Testing Management
Version Control