A cloud-based data integration service that allows users to create data-driven workflows for orchestrating and automating data movement and data transformation. It supports hybrid data integration and provides a rich set of data connectors.
Tools that enable data flows between different systems within the organization and with external parties such as custodians, fund administrators, and market data providers through APIs, ETL processes, and messaging.
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API Connectivity Capability to connect and interact with other systems via APIs (REST, SOAP, etc.). |
Azure Data Factory (ADF) provides REST API endpoints and .NET SDK for management and pipeline execution, fulfilling API connectivity. | |
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Pre-built Connectors Availability of pre-built connectors to common fund systems, custodians, administrators, and data vendors. |
ADF offers a large selection of pre-built connectors to databases, SaaS apps, cloud services, and on-premises sources. | |
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Custom Connector Support Ability to build custom data connectors/adapters. |
ADF allows for custom connectors using REST, HTTP, and generic interfaces. | |
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File-based Integration Supports integration via file exchange (CSV, XML, XLS, etc.). |
ADF supports file-based data ingestion (CSV, XML, JSON, Excel) via integration runtimes. | |
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Message Queue Integration Integration with messaging systems/brokers (MQ, Kafka, RabbitMQ). |
Not as far as we are aware.* ADF does not natively support direct MQ/Kafka/RabbitMQ integration, though workaround pipelines may be constructed. | |
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FTP/SFTP Capabilities Ability to send/receive data via FTP or SFTP protocols. |
ADF supports FTP and SFTP as data sources and sinks. | |
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Webhooks Support Supports event-driven integrations via webhooks. |
ADF supports event triggers and can invoke or be invoked via webhooks. | |
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Batch vs. Real-time Processing Flexible support for both batch and real-time data integration. |
ADF supports both batch and near-real-time (with event and scheduled triggers) data movement and transformation. | |
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Data Source Auto-Discovery Automated recognition and onboarding of new data sources. |
No information available | |
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Partner Network Ecosystem of certified integration partners. |
Microsoft partners with a network of certified Azure integration partners. | |
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Number of Supported Systems Total number of different systems/platforms supported for integration. |
No information available | |
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Simultaneous Connections Maximum concurrent data connections supported. |
No information available | |
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API Throughput Maximum number of API calls handled per second. |
No information available |
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Visual Data Mapping Graphical tools for defining data transformation and mapping. |
Visual data mappings are available using the Data Flow feature in ADF UI. | |
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Scripting/Custom Logic Ability to include scripts or custom logic in data pipelines. |
Script activity and expressions in ADF support custom logic in data pipelines. | |
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Data Validation Rules Built-in validation of data formats, types, and constraints. |
Data validation activities can be set on data sources and in mapping data flows. | |
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Error Handling & Logging Comprehensive error tracking and data issue logging mechanisms. |
ADF provides error logging and monitoring through Azure Monitor integration. | |
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Automated Data Cleansing Capabilities to auto-correct or flag suspect data. |
ADF offers data cleansing transformations (e.g., remove nulls, fuzzy matching) in mapping data flows. | |
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Data Enrichment Ability to enhance datasets with reference or market data. |
Data enrichment (e.g., lookup, join with reference data) is possible in ADF data flows. | |
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Reprocessing Failed Batches Supports automated or manual rerun of failed data batches. |
Failed pipeline runs can be re-executed manually or automatically. | |
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Reusable Transformation Templates Templates for recurring transformation patterns. |
Templates for data flows and activities can be stored and reused. | |
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Auditable Transformation Steps Transformation history and audit logging for compliance. |
ADF logging/auditing provides traceability for transformation steps. | |
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Parallel Processing Concurrency in executing ETL jobs. |
ADF jobs can leverage multiple integration runtimes in parallel. | |
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Job Runtime Average time taken to run an ETL job. |
No information available | |
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Supported Data Types Number of structured/semi-structured/unstructured data types supported. |
No information available |
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Data Lineage Tracing data origin, transformations, and flow. |
ADF provides data lineage via integration with Azure Purview. | |
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Data Catalog Central registry of available data and sources. |
Integration with Azure Purview allows ADF to expose a data catalog. | |
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Quality Metrics Dashboard Visualization of data quality indicators (completeness, accuracy, timeliness, etc.). |
No information available | |
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Automated Anomaly Detection Identifying data outliers or issues automatically. |
No information available | |
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Data Versioning Version control for datasets and schemas. |
ADF supports versioning of pipeline definitions; Azure Data Lake and Purview offer data versioning. | |
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Master Data Management Ensures unique and consistent master data across systems. |
ADF supports MDM via data flow and Azure ecosystem (Purview, SQL). | |
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Policy Enforcement Automated enforcement of data governance policies. |
Policy enforcement is available with Azure Policy, Purview, and ADF integration. | |
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Stewardship Workflows Tools for data stewards to manage and resolve issues. |
ADF integrates with Azure Purview to support stewardship workflows. | |
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Regulatory Reporting Support Facilitates compliance with industry and regulatory standards. |
ADF supports regulatory reporting via templates, and Azure compliance certifications. | |
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Data Retention Policy Controls Configuration of record retention and disposal schedules. |
ADF can enforce retention via integration with Azure policies. | |
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Role-based Data Access Restricts actions/visibility based on user/group roles. |
ADF provides role-based access through Azure Active Directory integration. | |
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Access Audit Logs Detailed logging of data access and modifications. |
All access and activity is logged via Azure Monitor and can be audited. |
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Data Encryption In-Transit Encryption of all data during transfer between systems. |
Data is encrypted using TLS during transfer. | |
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Data Encryption At-Rest Encryption of stored data on disk/databases. |
Azure-at-rest encryption applies to all stored data in ADF. | |
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Multi-factor Authentication Multi-factor login for users and administrators. |
ADF inherits Multi-factor Authentication from Azure AD for access. | |
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User Access Controls Fine-grained control over user permissions and roles. |
User and admin permissions are finely controlled via Azure RBAC. | |
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Audit Trail Complete logging of all user and system activities. |
All operations are logged centrally via Azure Monitor and diagnostic settings. | |
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Compliance Certifications Adherence (and certifications) to standards like ISO 27001, SOC 2, GDPR. |
ADF, as part of Azure, supports SOC 2, ISO 27001, GDPR and other standard certifications. | |
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Secure API Authentication Token-based or certificate-based authentication for APIs. |
ADF supports OAuth2, certificate, and managed identity-based API authentication. | |
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Penetration Testing Practices Regular security testing for vulnerabilities. |
Azure regularly performs penetration and vulnerability testing. | |
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Data Masking/Redaction Ability to mask or redact sensitive data in outputs. |
Sensitive data masking and Purview data classification available. | |
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Incident Response Mechanisms Pre-defined procedures for data breaches or security incidents. |
Azure/ADF provides defined DR plans and incident response procedures. | |
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Automated Compliance Monitoring Continuous monitoring for regulatory compliance violations. |
ADF can use Azure Policy to monitor for compliance violation events. | |
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Retention Policy Enforcement Automated enforcement of data retention and document destruction policies. |
Retention policies are automated via the Azure platform. |
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Horizontal Scalability Ability to scale out across multiple servers or cloud instances. |
ADF leverages Azure’s horizontal scalability features in cloud deployments. | |
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Vertical Scalability Ability to add resources (CPU, RAM, Storage) to improve performance. |
ADF pipelines can be scaled vertically via increased pipeline or integration runtime resources. | |
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Data Throughput Maximum volume of data processable per unit time. |
No information available | |
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Latency Average time taken to process a transaction or data record. |
No information available | |
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Concurrency Support Number of data flows/pipelines that can run in parallel. |
No information available | |
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High Availability Built-in failover and redundancy for uninterrupted service. |
ADF offers high availability as a managed Azure service with built-in redundancy. | |
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Load Balancing Distributes workloads evenly for optimal resource usage. |
ADF integrates with Azure Load Balancer; workloads are distributed across runtimes. | |
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Auto-scaling Automatic adjustment of resources based on workload. |
Auto-scaling is available for Integration Runtime resources. | |
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Processing Window Size Configurable time window for batch processing. |
No information available | |
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Transaction Volume Capacity Maximum volume of transactions supported per day. |
No information available |
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Real-time Health Dashboard Live display of system health and key metrics. |
Real-time monitoring visualizations and dashboards are available within the Azure portal. | |
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Custom Alerts User-configurable monitoring rules and thresholds. |
ADF supports custom/threshold-based alerts through integration with Azure Monitor and Logic Apps. | |
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Historical Data Analytics Tools for reviewing past trends and incidents. |
ADF logs and activity history support analytics on historical pipeline executions. | |
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Error Notification Channels Multiple channels for error alerts (email, SMS, Slack, etc.). |
Alerts/notifications are configurable for email, SMS, webhooks, etc. | |
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Automated Remediation Rules to auto-resolve common issues or trigger workflows. |
Automated remediation can be achieved using Logic Apps or Functions upon alert triggers. | |
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Usage Analytics Reports on platform usage and performance. |
ADF usage analytics available through Azure monitoring and reporting. | |
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User Activity Logging Detailed tracking of all user activities. |
User and system activity logging is available via Azure and ADF logs. | |
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Customizable Reporting Support for building and scheduling custom reports. |
Custom reporting can be built using Azure Monitor, Power BI, or custom export. | |
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MTTR Tracking Time to detect and resolve technical incidents. |
No information available | |
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Alert Response Time Time for alerts to be delivered to responsible parties. |
No information available |
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No-code/Low-code Pipeline Builder Drag-and-drop interface for building data flows without programming. |
ADF UI features a drag-and-drop, no-code/low-code authoring experience for data pipelines. | |
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Role-based Dashboards User interfaces tailored for different user types (IT, Ops, Business, etc.) |
ADF dashboard adapts UI to different role types (admin, developer, ops) via Azure role mapping. | |
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Self-service Data Ingestion Allow non-technical users to upload and ingest data. |
Self-service ingestion is available for users with the appropriate permissions. | |
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Template Library Library of pre-built templates for common data flows and use cases. |
ADF Gallery and Azure Marketplace feature pre-built pipeline templates. | |
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Customizable Workspaces Users can personalize workspace layouts, filters, and views. |
ADF UX can be personalized by individual users (layout, filters, favorite pipelines). | |
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Inline Help & Documentation Integrated help, tooltips, and user guides. |
Integrated help, tooltips, and Microsoft Learn documentation embedded in UI. | |
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Approval Workflows Request/approve changes to pipelines and integrations. |
Pipeline publish, approval, and change review workflows are supported via Git integration. | |
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Bulk Operations Manage multiple records/files in one action. |
Bulk data processing and pipeline management operations supported. | |
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Search & Filtering Powerful search and filtering of data and workflows. |
ADF provides search and filtering in the UI for pipelines, datasets, triggers. | |
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Mobile Accessibility Mobile-friendly or dedicated mobile applications. |
ADF Studio is web-based and accessible on tablets, but not a dedicated mobile app. |
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Cloud Deployment Support Native support for cloud deployment (AWS, Azure, GCP). |
ADF can be provisioned on Azure (native cloud) and integrates with multi-cloud services. | |
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On-premises Installation Support for on-premises or private cloud environments. |
No information available | |
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Hybrid Deployment Ability to operate across both cloud and on-premises infrastructure. |
Hybrid data integration supported via self-hosted integration runtime. | |
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Multi-tenancy Supports logical separation for different teams or clients. |
ADF supports multi-tenancy via subscription, RBAC and governance controls. | |
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Microservices Architecture System is designed with microservices for modularity and resilience. |
ADF has a modular, distributed architecture in the cloud ecosystem, but is not strictly microservices in classic style. | |
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Disaster Recovery Capabilities Automatic failover and backup/restore for business continuity. |
Azure Backup and DR capabilities available across the service. | |
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Containerization Support Support for Docker, Kubernetes, and similar technologies. |
ADF supports deployment within Docker containers and orchestration with Kubernetes (via Azure Data Factory Managed Virtual Network Integration). | |
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Multi-region Support Ability to operate across multiple geographic regions/data centers. |
ADF is available in many Azure regions supporting multi-region deployment and failover. | |
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Zero-downtime Upgrades Apply platform upgrades without interrupting service. |
Upgrades are managed by Azure and conducted without downtime. | |
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Resource Auto-provisioning Automated deployment and resource allocation. |
Resource allocation and auto-provisioning are managed dynamically in the cloud. |
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24/7 Technical Support Round-the-clock access to expert technical support. |
Microsoft offers 24/7 support plans for ADF. | |
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Dedicated Account Manager A single point of contact for relationship management. |
Enterprise/Premium support packages include a dedicated Microsoft account manager. | |
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Community Forums Engaged user community for peer support. |
Active Azure and ADF user communities and forums are available. | |
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Extensive Documentation Detailed guides, manuals, and reference materials. |
Extensive Microsoft and third-party documentation is available for ADF. | |
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Regular Product Updates Frequent improvements and new feature releases. |
ADF receives regular feature updates and improvements; see Azure blog. | |
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Training & Certification Availability of certifications and formal training programs. |
Microsoft Learn and third-party training courses/certification are available for ADF. | |
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Partner/Marketplace Ecosystem Third-party integrations, add-ons, and certified partners. |
ADF supports ecosystem integration via Azure Marketplace. | |
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Service Level Agreements (SLAs) Contractual performance and availability guarantees. |
SLAs are guaranteed and published for ADF. | |
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Customer Success Programs Proactive guidance to help clients realize value. |
Microsoft offers customer success/support initiatives. | |
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Multi-language Support Availability of user interfaces and documentation in multiple languages. |
ADF documentation and Azure portal are available in multiple languages. |
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Usage-based Pricing Pricing model based on consumption (e.g., data processed, transactions, users). |
ADF is billed by usage (data movement, activities, pipeline runs, etc.). | |
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Flexible License Models Options for perpetual, subscription, or pay-as-you-go licenses. |
Subscription and pay-as-you-go are both available for ADF on Azure. | |
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Transparent Pricing Clear, upfront pricing without hidden fees. |
ADF pricing calculator provides transparent upfront cost breakdowns. | |
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Trial/Evaluation Period Available free trial or PoC before commitment. |
ADF offers 30-day free trials with Azure. | |
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Volume Discounts Discounts for larger usage or enterprise agreements. |
Not as far as we are aware.* Microsoft typically does not offer explicit volume discounts for ADF, although enterprise Azure agreements may include them. | |
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Support Cost Inclusions Support and maintenance included in standard fees. |
No information available | |
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Cost Predictability Ability to forecast and control total cost of ownership. |
ADF provides cost calculators and allows budgeting/alerting for predictability. | |
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Automated Billing Self-service billing and invoicing. |
Self-service billing via the Azure portal. | |
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Cost Optimization Tools Built-in analytics to optimize platform usage and minimize cost. |
Azure Cost Management tools are available to monitor and optimize ADF usage. | |
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Multi-currency Pricing Support Ability to quote and bill in multiple currencies. |
Azure subscriptions support billing in multiple currencies. |
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Plugin/Extension Framework Ability to extend core functionality via custom plugins/extensions. |
ADF can be extended with custom .NET/PowerShell scripts and Azure Functions. | |
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Custom Workflow Support Build and deploy custom data workflows and processes. |
Custom pipeline and workflow support is possible in ADF, with extensibility through Logic Apps and Azure Functions. | |
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API for Custom Integrations Well-documented APIs for extending and integrating with external tools. |
ADF management APIs are fully documented for integration and extension. | |
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White-labeling Ability to customize branding and user interface. |
No information available | |
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Custom Roles & Permissions Define new user roles and granular access configurations. |
Custom roles and permissions are supported via Azure RBAC and ADF permissions. | |
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Scripting Language Support Built-in support for languages like Python or JavaScript for user scripts. |
Data Flows support expressions—ADF supports custom scripting (limited) through U-SQL, Data Flows, and Azure Functions. | |
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UI Theming and Customization Configure appearance and user interface elements. |
No information available | |
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Event Hooks Custom logic triggered on data events or system actions. |
Event-based triggers and Logic Apps integration allow user-defined event hooks. | |
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Open Standards Compliance Built with and extends using open industry standards. |
ADF uses open standards for data transport (REST, OData); industry standards are promoted in pipeline design. | |
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Integration SDK Software development kit for building deep integrations. |
SDKs are available for .NET, Python, and REST for ADF deep integrations. |
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