About
AnalyticsCreator is a metadata-driven design application for data warehouse automation and data product engineering across the Microsoft data stack.
At its core is the AnalyticsCreator Governed Control Model, which keeps business meaning, data structures, transformation rules, dependencies and technical implementation connected in one controlled project model. Data teams design the required architecture in AnalyticsCreator, then generate native Microsoft assets from that design.
Generated assets can include SQL Server objects, SSIS packages, Azure Data Factory pipelines, Microsoft Fabric components, deployment artefacts and Power BI semantic models. AnalyticsCreator supports dimensional, 3NF and hybrid modelling approaches together with ingestion, transformations, delta loading, historisation, Slowly Changing Dimensions, snapshots and repeatable data-processing patterns.
Changes made in the model can be propagated across dependent project assets, while lineage, documentation and impact analysis remain connected to the underlying design. This helps teams reduce repetitive engineering work, standardise delivery and understand the effect of change before regenerating affected assets.
AnalyticsCreator generates native Microsoft technology rather than requiring a proprietary runtime. Organisations retain ownership of the resulting implementation and can integrate generated assets into existing Git, Azure DevOps and CI/CD processes.
Design Intelligence extends this governed project context into AI-assisted data engineering by giving authorised AI tools and agents structured access to metadata, lineage, dependencies and design rules.
Typical use cases include enterprise data warehouse development, Microsoft Fabric adoption, SQL Server and SSIS modernisation, governed Power BI delivery, SAP-to-Microsoft analytics architectures and repeatable data product engineering.
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About
SCIKIQ is an AI-native Data & Intelligence Platform designed to help enterprises make their data trusted, governed, connected, and ready for AI in weeks rather than years. Recognized by Forrester, NASSCOM League of 10, YourStory Tech30, Inc42, and DataIQ, SCIKIQ supports enterprises across the USA, India, UK, and UAE.
SCIKIQ brings together Data Integration, Data Quality, Data Governance, Metadata Management, Data Lineage, Semantic Intelligence, Knowledge Graphs, Conversational Analytics, Generative AI, Data Products, and AI Agents within one unified platform.
Unlike traditional data platforms that often require extensive replatforming or migration, SCIKIQ works with an enterprise’s existing technology ecosystem. Organizations can connect SAP, Salesforce, Oracle, Snowflake, Databricks, AWS, Azure, GCP, data lakes, data warehouses, and enterprise applications through 200+ pre-built connectors, without rip-and-replace.
Contextual Intelligence at the Core
SCIKIQ goes beyond connecting data by helping AI understand the business context behind it.
Its semantic intelligence layer brings together business terminology, KPI definitions, metadata, lineage, ownership, business rules, ontologies, and relationships to create a trusted context layer for enterprise analytics and AI.
Business users can ask questions in natural language, investigate KPIs, identify root causes, and generate insights without writing SQL. Data teams gain enterprise-grade capabilities for data integration, quality, governance, lineage, metadata, and control.
AI teams gain trusted, contextual enterprise data for building Generative AI applications, copilots, and intelligent AI agents.
Why Enterprises Choose SCIKIQ
AI-ready in 3–6 weeks | 200+ connectors | 99.9% availability | No-code | Multi-cloud | No vendor lock-in | No replatforming
SCIKIQ has production deployments across industries including manufacturing, retail, aviation, logistics, BFSI, healthcare, and other data-intensive enterprises.
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Platforms Supported
Windows
Supported
Mac
Not Supported
Linux
Not Supported
Cloud
Supported
On-Premises
Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Platforms Supported
Windows
Supported
Mac
Supported
Linux
Supported
Cloud
Not Supported
On-Premises
Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Audience
Data Engineers, Data Architects, BI Engineers, Analytics Engineers, Heads of Data, BI Leads, Microsoft Data Platform Teams
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Audience
BFSI, Manufacturing, Logistics, Retail, Healthcare and others
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Support
Phone Support
Supported
24/7 Live Support
Not Supported
Online
Supported
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Support
Phone Support
Supported
24/7 Live Support
Supported
Online
Supported
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API
Offers API
Not Supported
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API
Offers API
Supported
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Screenshots and Videos |
Screenshots and Videos |
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PricingPricing for AnalyticsCreator depends on deployment size, number of environments, and user licenses required. Contact AnalyticsCreator’s sales team for a tailored quote based on your organization's data engineering needs.
Free Version
Not Supported
Free Trial
Supported
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PricingYearly License
Contract Pricing
Free Version
Not Supported
Free Trial
Not Supported
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Reviews/
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Reviews/
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Training
Documentation
Supported
Webinars
Supported
Live Online
Supported
In Person
Not Supported
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Training
Documentation
Supported
Webinars
Supported
Live Online
Supported
In Person
Supported
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Company InformationAnalyticsCreator
Germany
www.analyticscreator.com
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Company InformationSCIKIQ
Founded: 2023
India
scikiq.com
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Alternatives |
Alternatives |
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CategoriesAnalyticsCreator is a metadata-driven design application for Microsoft data engineering teams. Engineers define structures, transformations, loading logic and dependencies centrally, then generate native SQL, SSIS, Azure Data Factory, Microsoft Fabric and Power BI assets. Repeatable patterns for ingestion, transformation, historisation, SCD processing and deployment reduce manual engineering while keeping lineage, documentation and change impact connected to the project design. AnalyticsCreator provides metadata-driven design and generation for data integration across Microsoft environments. Teams define sources, mappings, transformations, dependencies and loading rules centrally, then generate native SQL, SSIS and Azure Data Factory implementation assets. This helps standardise recurring integration patterns while preserving lineage, documentation and ownership of the resulting Microsoft technology. AnalyticsCreator helps Microsoft data teams design governed ingestion and transformation processes for data lake and analytical architectures. Metadata-defined sources, mappings, transformations and dependencies can be used to generate native Microsoft implementation assets for supported Azure and Microsoft Fabric scenarios. AnalyticsCreator provides the design and generation layer rather than acting as the data lake runtime itself. AnalyticsCreator captures lineage as part of the engineering model rather than as a separate documentation exercise. Sources, tables, transformations, references and downstream analytical structures remain connected through project metadata, allowing teams to trace data movement and understand dependencies across the solution. Lineage can also support impact analysis when models or transformations change. AnalyticsCreator helps Microsoft data teams manage the design and evolution of structured data estates through a central metadata model. Sources, schemas, tables, relationships, transformations and dependencies remain connected to the generated implementation. This provides greater visibility into project structure, lineage and change impact while helping teams apply consistent modelling and engineering standards. AnalyticsCreator provides model-driven design for data warehouses and data products across the Microsoft data stack. Teams can define dimensional, 3NF and hybrid models together with relationships, transformations, historisation rules and dependencies. The approved model then drives generation of native SQL, pipelines, documentation, semantic models and deployment artefacts, keeping design and implementation aligned as the project changes. Accelerate the development of your data warehouses by automating complex model designs, including dimensional, data mart, and data vault architectures. AnalyticsCreator enhances scalability for large data environments and ensures better governance through its automated features. Generate optimized code for leading platforms such as Snowflake, Azure Synapse, and MS Fabric. Improve data quality, consistency, and governance throughout the data warehouse lifecycle with automated tools for schema evolution and historical data handling. Enhance collaboration with version control and automated documentation, enabling seamless teamwork and rapid iteration. Leverage AnalyticsCreator to meet the demands of modern data warehouse development with CI/CD and agile workflows, reducing development cycles significantly. AnalyticsCreator provides metadata-driven design and generation for ETL and ELT processes across the Microsoft data stack. Data teams define mappings, transformations, loading logic, dependencies and historisation centrally, then generate native SQL procedures, SSIS packages and Azure Data Factory pipelines. Reusable patterns support ingestion, delta loading, SCD processing and repeatable transformations without introducing a proprietary production runtime. Metadata is the foundation of AnalyticsCreator. The central project model connects data structures, transformations, business rules, relationships, dependencies, lineage, documentation and generated implementation. This allows data teams to use metadata not only to describe a solution, but to actively drive generation, change analysis and controlled delivery across Microsoft data projects. AnalyticsCreator can generate governed analytical and semantic models for Microsoft Power BI and Analysis Services from the same metadata used to design the underlying data warehouse. Relationships, dimensions and model structures remain connected to the wider project design, helping teams keep analytical models aligned with upstream data structures and dependencies. |
CategoriesSCIKIQ is an AI-native Agentic Data Management platform that transforms enterprise data into governed, reusable and AI-ready Data Products. At its core is the SCIKIQ Data Product Factory and Data Marketplace, built to operationalize Data-as-a-Product across the enterprise. The Data Product Factory enables teams and AI Agents to discover, create, govern, enrich and publish Data Products using trusted enterprise data, business context, semantics, quality and lineage. SCIKIQ Data Marketplace provides an internal and external marketplace to discover, share, consume and monetize Data Products, datasets, APIs, KPIs, analytics and AI-ready assets. Key capabilities include Agentic Data Management, Data Products, Data Product Factory, Data Marketplace, Data-as-a-Product, Data Mesh, Self-Service Data, Data Catalog, Data Governance, Data Quality, Data Lineage, Data Semantics, APIs and AI Agents. From raw enterprise data to governed Data Products—built for Analytics, Generative AI and Recognized among the Top 34 AI-Augmented platforms globally by Forrester and ranked among India’s Top 10 DeepTech companies in AI & Analytics by NASSCOM, SCIKIQ is an AI-native Big Data and enterprise data platform built for the AI era. SCIKIQ connects and unifies data across SAP, databases, data warehouses, data lakes, cloud platforms, enterprise applications, and APIs without requiring organizations to replace or migrate their existing data stack. It creates a trusted, governed and AI-ready data foundation for Big Data, analytics, Business Intelligence, and enterprise AI. Key capabilities include Big Data integration, ETL/ELT, data pipelines, data transformation, data lakehouse, data preparation, data quality, metadata management, data catalog, data governance, data lineage, semantic intelligence, real-time analytics, and AI-powered analytics. With support for cloud, hybrid, and on-premise environments, SCIKIQ helps enterprises move faster to Generative AI and Agentic AI. Recognized among the Top 34 AI-Augmented Business Intelligence platforms globally by Forrester, SCIKIQ is an AI-native Business Intelligence platform built for the next generation of enterprise decision-making. SCIKIQ brings Business Intelligence, enterprise analytics, Conversational AI, dashboards, data integration, governance, semantic intelligence, and Agentic AI together on a unified platform. It enables organizations to transform enterprise data into trusted, contextual, and AI-ready intelligence—without replacing their existing technology stack. Built for enterprise-wide BI, SCIKIQ connects data across SAP, databases, data warehouses, cloud platforms, Power BI, Tableau, and business applications to create a connected intelligence layer. Key capabilities include AI-powered Business Intelligence, Conversational Analytics, Enterprise 360, self-service BI, KPI analytics, semantic intelligence, data visualization, real-time analytics, data governance, data lineage & AI agents SCIKIQ is an AI-native Data Catalog platform built to help enterprises discover, understand, govern and activate data for Analytics and AI. SCIKIQ combines Data Catalog, Data Discovery, Metadata Management, Data Lineage, Data Quality, Business Glossary and Data Semantics in one intelligent platform. Automatically catalog data across SAP, databases, data warehouses, data lakes, cloud platforms, APIs and enterprise applications. Search and discover datasets, tables, columns, metadata, business terms, KPIs, owners, relationships and lineage from a unified enterprise data catalog. Key capabilities include Automated Data Cataloging, Metadata Discovery, Metadata Management, Business Glossary, Data Classification, Data Profiling, Data Search, Data Lineage, Data Governance, Data Quality and Semantic Layer. SCIKIQ connects technical metadata with business meaning and context, creating a trusted catalog for Data Management, Business Intelligence, Generative AI and Agentic AI. SCIKIQ is an AI-native Data Discovery platform that helps enterprises find, understand, classify and trust data across complex data environments. SCIKIQ combines Data Discovery, Data Catalog, Metadata Management, Data Search, Data Lineage, Data Profiling, Data Classification and Data Semantics in one unified platform. Automatically discover data across SAP, databases, data warehouses, data lakes, cloud platforms, APIs and enterprise applications. Search and explore datasets, tables, columns, metadata, business terms, KPIs and relationships through intelligent enterprise data discovery. SCIKIQ combines automated metadata discovery with best-in-class Data Lineage, Data Quality and a world-leading Data Semantics practice to provide business context behind enterprise data. Built for Data Discovery, Data Governance, Data Management, Data Cataloging, Business Intelligence, Analytics, Generative AI and Agentic AI. Recognized among the Top 34 AI-Augmented platforms globally by Forrester and India’s Top 10 DeepTech companies in AI & Analytics by NASSCOM, SCIKIQ is an AI-native Enterprise Data Fabric built ground-up for AI. SCIKIQ creates a unified, intelligent data layer across SAP, databases, data warehouses, data lakes, cloud, APIs and enterprise applications—without migration, replatforming or replacing the existing data stack. SCIKIQ Data Fabric combines Data Integration, ETL/ELT, Data Pipelines, Data Quality, Data Governance, Data Catalog, Metadata Management, Data Lineage, Master Data Management, Data Observability and Data Semantics. Its world-leading Data Semantics practice connects technical data with business context, KPIs, relationships and meaning—creating an AI-ready enterprise data foundation. Built for Data Fabric, Data Management, Business Intelligence, Analytics, Generative AI and Agentic AI. SCIKIQ is ranked alongside leading Data Governance platforms globally, with best-in-class Data Lineage, Data Quality and a world-leading Data Semantics practice. SCIKIQ delivers enterprise Data Governance, automated Data Lineage, Data Quality, Data Catalog, Metadata Management, Business Glossary, Data Discovery, Data Classification, Data Profiling, Data Observability, PII Management, Policy Management, Data Compliance and AI Governance in one platform. Track end-to-end Data Lineage across SAP, databases, data warehouses, data lakes, cloud, ETL pipelines, BI dashboards and enterprise applications. Improve Data Quality through automated profiling, validation, monitoring and quality rules. SCIKIQ Data Semantics connects metadata, business terms, KPIs, relationships and enterprise context to create trusted, AI-ready data. Built for Data Governance, Data Management, Regulatory Compliance, Business Intelligence, Generative AI and Agentic AI. SCIKIQ Data Hub is AI-native Data Management Platform built ground-up for AI and designed to be the fastest path from enterprise data to Enterprise AI. Recognized among the Top 34 AI-Augmented platforms globally by Forrester and India’s Top 10 DeepTech companies in AI & Analytics by NASSCOM, SCIKIQ connects, governs and activates data across the enterprise. Integrate data from SAP, databases, data warehouses, data lakes, cloud platforms, APIs and enterprise applications without replatforming or disrupting your existing data stack. Built-in Data Governance, Data Quality, Data Catalog, Metadata Management and Data Lineage create trusted data by design. ETL/ELT, Data Integration, Data Pipelines, Data Transformation, Data Preparation and Semantic Intelligence turn fragmented data into a connected, AI-ready foundation. Built for Analytics, Business Intelligence, Generative AI and Agentic AI, SCIKIQ helps enterprises move from siloed data to trusted intelligence in weeks not years. SCIKIQ delivers best-in-class Data Quality for enterprises that need trusted, accurate and AI-ready data. Built ground-up for AI, SCIKIQ combines Data Quality Management, Data Profiling, Data Cleansing, Data Validation, Data Monitoring and Data Observability across complex enterprise data environments. SCIKIQ provides automated Data Quality Rules, Data Validation, Data Standardization, Data Matching, Deduplication, Data Enrichment, Data Completeness, Accuracy Checks, Consistency Checks, Anomaly Detection and Data Quality Monitoring. Continuously measure and improve data quality across SAP, databases, data warehouses, data lakes, cloud platforms, ETL pipelines and enterprise applications. Integrated Data Lineage, Data Governance, Metadata Management and Data Semantics help identify where quality issues originate and understand their business impact. Trusted Data. Better Analytics. Reliable AI. SCIKIQ is an AI-native ETL and ELT platform for fast, scalable enterprise Data Integration and Data Transformation. Build, automate and manage ETL pipelines across cloud, on-premise and hybrid data environments with no-code and AI-assisted automation. SCIKIQ combines ETL, ELT, Data Pipelines, Data Integration, Data Ingestion, Data Extraction, Data Transformation, Data Loading, Data Mapping, Data Migration, Data Replication, Change Data Capture (CDC), Batch Processing and Real-Time Data Integration. Connect SAP, ERP, CRM, databases, data warehouses, data lakes, SaaS applications, APIs, files and streaming data through 200+ pre-built connectors. Built-in Data Quality, Data Governance, Data Lineage, Metadata Management and Data Observability help create trusted pipelines and AI-ready data. From traditional ETL to modern ELT, real-time pipelines and AI-powered integration, SCIKIQ provides one platform to move, transform and activate enterprise data. SCIKIQ is an AI-native Data Integration platform built to connect, move and transform enterprise data across any system, cloud or environment. From ETL/ELT and real-time data pipelines to SAP Integration and API Integration, SCIKIQ provides a unified platform for modern enterprise data integration. Connect SAP S/4HANA, SAP ECC, databases, data warehouses, data lakes, SaaS applications, APIs, files and streaming sources using 200+ pre-built connectors. Build no-code data pipelines for batch, micro-batch, real-time streaming and Change Data Capture (CDC) across cloud, on-premise and hybrid environments. SCIKIQ also includes an API Hub to create, manage, govern and reuse enterprise APIs, helping organizations connect applications, data and AI services through a common integration layer. With No-code platform & built-in Data Quality, Data Governance, Data Lineage, Observability and AI-assisted automation, SCIKIQ goes beyond traditional ETL software to deliver trusted, AI-ready data. SCIKIQ is an AI-native Master Data Management (MDM) platform built to create trusted, unified and AI-ready master data across the enterprise. SCIKIQ combines Master Data Management, MDM, Data Quality, Data Governance, Data Integration and Data Semantics in one platform. Create a trusted Golden Record and Single Source of Truth across customers, products, suppliers, vendors, employees and other business entities. SCIKIQ supports Customer 360, Product 360, Supplier 360, Multi-Domain MDM, Reference Data Management and Hierarchy Management. Key capabilities include Entity Resolution, Data Matching, Deduplication, Data Cleansing, Data Standardization, Data Validation, Data Enrichment, Data Profiling, Data Stewardship, Metadata Management and Data Lineage. Connect master data across SAP, ERP, CRM, databases, data warehouses, cloud and enterprise applications to power Analytics, Business Intelligence, Generative AI and Agentic AI. |
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Data Lineage Features
Database Change Impact Analysis
Supported
Filter Lineage Links
Supported
Implicit Connection Discovery
Supported
Lineage Object Filtering
Supported
Object Lineage Tracing
Supported
Point-in-Time Visibility
Supported
User/Client/Target Connection Visibility
Not Supported
Visual & Text Lineage View
Supported
Data Management Features
Customer Data
Supported
Data Analysis
Supported
Data Capture
Not Supported
Data Integration
Supported
Data Migration
Supported
Data Quality Control
Supported
Data Security
Supported
Information Governance
Supported
Master Data Management
Supported
Match & Merge
Not Supported
ETL Features
Data Analysis
Supported
Data Filtering
Supported
Data Quality Control
Not Supported
Job Scheduling
Not Supported
Match & Merge
Supported
Metadata Management
Supported
Non-Relational Transformations
Supported
Version Control
Supported
Data Warehouse Features
Ad hoc Query
Supported
Analytics
Supported
Data Integration
Supported
Data Migration
Supported
Data Quality Control
Not Supported
ETL - Extract / Transfer / Load
Supported
In-Memory Processing
Not Supported
Match & Merge
Not Supported
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Data Management Features
Customer Data
Supported
Data Analysis
Supported
Data Capture
Supported
Data Integration
Supported
Data Migration
Supported
Data Quality Control
Supported
Data Security
Supported
Information Governance
Supported
Master Data Management
Supported
Match & Merge
Supported
ETL Features
Data Analysis
Supported
Data Filtering
Supported
Data Quality Control
Supported
Job Scheduling
Supported
Match & Merge
Supported
Metadata Management
Supported
Non-Relational Transformations
Supported
Version Control
Supported
Big Data Features
Collaboration
Supported
Data Blends
Supported
Data Cleansing
Supported
Data Mining
Supported
Data Visualization
Supported
Data Warehousing
Supported
High Volume Processing
Supported
No-Code Sandbox
Supported
Predictive Analytics
Supported
Templates
Supported
Business Intelligence Features
Ad Hoc Reports
Supported
Benchmarking
Supported
Budgeting & Forecasting
Supported
Dashboard
Supported
Data Analysis
Supported
Key Performance Indicators
Supported
Natural Language Generation (NLG)
Supported
Performance Metrics
Supported
Predictive Analytics
Supported
Profitability Analysis
Supported
Strategic Planning
Supported
Trend / Problem Indicators
Supported
Visual Analytics
Supported
Data Discovery Features
Contextual Search
Supported
Data Classification
Supported
Data Matching
Supported
False Positives Reduction
Supported
Self Service Data Preparation
Supported
Sensitive Data Identification
Supported
Visual Analytics
Supported
Data Fabric Features
Data Access Management
Supported
Data Analytics
Supported
Data Collaboration
Supported
Data Lineage Tools
Supported
Data Networking / Connecting
Supported
Metadata Functionality
Supported
No Data Redundancy
Supported
Persistent Data Management
Supported
Data Governance Features
Access Control
Supported
Data Discovery
Supported
Data Mapping
Supported
Data Profiling
Supported
Deletion Management
Supported
Email Management
Supported
Policy Management
Supported
Process Management
Supported
Roles Management
Supported
Storage Management
Supported
Data Quality Features
Address Validation
Supported
Data Deduplication
Supported
Data Discovery
Supported
Data Profililng
Supported
Master Data Management
Supported
Match & Merge
Supported
Metadata Management
Supported
Integration Features
Dashboard
Supported
ETL - Extract / Transform / Load
Supported
Metadata Management
Supported
Multiple Data Sources
Supported
Web Services
Supported
Master Data Management Features
Data Governance
Supported
Data Masking
Supported
Data Source Integrations
Supported
Hierarchy Management
Supported
Match & Merge
Supported
Metadata Management
Supported
Multi-Domain
Supported
Process Management
Supported
Relationship Mapping
Supported
Visualization
Supported
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Integrations
Hadoop
Supported
PostgreSQL
Supported
SQL Server
Supported
Apache Kafka
Not Supported
Azure Analysis Services
Supported
Azure SQL Database
Supported
Azure Service Fabric
Supported
Dropbox
Not Supported
DuckDB
Supported
GitHub
Supported
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Integrations
Hadoop
Supported
PostgreSQL
Supported
SQL Server
Supported
Apache Kafka
Supported
Azure Analysis Services
Not Supported
Azure SQL Database
Not Supported
Azure Service Fabric
Not Supported
Dropbox
Supported
DuckDB
Not Supported
GitHub
Not Supported
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