Connectors: Connect to Any Data, Anywhere
Sparkflows provides a comprehensive library of built-in connectors to access data across files, databases, enterprise applications, cloud platforms, and streaming systems.
These connectors power end-to-end analytics, automation, and AI workflows, covering batch, incremental, and real-time data movement.
File Systems for Flexible Data Access
Sparkflows makes it easy to read and write data from both local and cloud-based file systems. Files can be ingested, prepared, and written back as part of automated workflows without custom scripting.
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Structured File Formats
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Work with CSV, JSON, Parquet, Excel, Avro, and Delta.
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Use structured data directly in analytics and automation workflows.
Unstructured File Formats
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Process text, PDFs, images, and binary files with ease.
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Enrich unstructured data and pass it downstream in workflows.
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Built for Automated Pipelines
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Move files through ingest, prepare, and output steps automatically.
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Reuse the same file connections across workflows and applications.
Databases and Data Platforms
Connect to relational, NoSQL, and analytical databases for reliable data access at scale. Sparkflows supports traditional databases, cloud data warehouses, and lakehouse platforms, enabling efficient querying, incremental ingestion, and bidirectional data movement.
These connectors are designed for both operational workloads and analytical processing.
Business and Enterprise Applications
Integrate data from business systems used across teams, including sales, marketing, finance, HR, and operations.
Application connectors allow data to flow seamlessly between enterprise tools and analytics workflows, keeping insights aligned with real-world business activity.
BI Tools and Analytics Destinations
Send prepared data directly to reporting and visualization tools.
Automated data feeds help keep dashboards and reports up to date, ensuring that insights reflect the latest available data without manual refresh cycles.
Streaming and Real-time Data
Work with real-time data streams using built-in streaming connectors. Sparkflows supports ingesting, processing, and writing streaming data for use cases such as monitoring, alerts, and near-real-time analytics.
Batch and streaming workflows can coexist within the same platform.
Connect to a Wide Range of Data Sources
Sparkflows connectors integrate effortlessly with data sources across traditional environments, modern data platforms, cloud warehouses, cloud databases, and enterprise applications.
Scale Faster with 100+ Connectors
Bring data together from every system. Keep platforms aligned and insights within reach.
Designed for Flexibility and Scale
Each connector is built to work with Sparkflows visual workflows while supporting advanced needs such as incremental loads, secure authentication, and enterprise governance.
When required, connectors can be extended or combined with custom logic using SQL, Python, or Spark without breaking the visual experience.
One Place to Discover and Connect
Sparkflows connectors are organized so teams can easily discover available systems, choose the right connector, and start building immediately.
As new platforms and technologies emerge, the connector ecosystem continues to expand, without disrupting existing workflows.
