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File-based connections let Planasonix ingest and deliver datasets as objects or streams over common protocols. You point at buckets, containers, or paths, attach credentials with the right cloud or protocol permissions, and reuse the same connection for multiple pipelines that share a landing zone or export folder.

Supported providers

Planasonix supports the following categories; exact capabilities depend on your connector edition. Object and blob storage
  • AWS S3 — Including cross-account access, SSE-KMS, and VPC endpoints where your network design requires them.
  • Azure Blob Storage — Including Azure Data Lake Storage Gen2 when accessed through the blob or DFS endpoints your connector exposes.
  • Google Cloud Storage (GCS) — Project-scoped buckets and uniform bucket-level access patterns.
  • Cloudflare R2 — S3-compatible API; set custom endpoint and signing options as required.
  • MinIO — Self-hosted or air-gapped S3-compatible deployments.
  • Wasabi — S3-compatible hot cloud storage with vendor-specific endpoint configuration.
Enterprise file and collaboration
  • Box — Folder- and enterprise-scoped content as exposed by the connector.
  • Microsoft OneDrive — Personal or work accounts via Microsoft Graph, per connector support.
  • Microsoft SharePoint — Sites, libraries, and drives as exposed by the connector.
Traditional transfer
  • FTP and SFTP — Partner and legacy systems; prefer SFTP when the server supports it.
S3-compatible vendors differ in IAM, region, path-style behavior, and signature versions. Always run Test connection and a small sample read after changing endpoint URLs or signing algorithms.

File format support

Planasonix connectors typically support structured and semi-structured file types for parse, split, and schema inference:
FormatTypical use
CSVExports from spreadsheets, mainframes, and flat-file exchanges; delimiter, quote, escape, and header options are configurable.
JSONAPI dumps, document exports, and newline-delimited JSON (NDJSON) event logs.
ParquetColumnar analytics handoffs; efficient for wide tables and nested data.
AvroSchema-evolving pipelines, often paired with Kafka or Hadoop-era ecosystems.
XMLEnterprise and industry feeds; row extraction depends on connector XPath or flattening options.
Compression (for example gzip, Snappy, ZSTD) is usually detected from object metadata or file extensions when you enable automatic decompression in the pipeline step.

Configure a storage connection

1

Select the provider connector

In Connections, choose New connection and pick S3, Azure Blob, GCS, or the protocol-specific tile (SFTP, Box, and so on).
2

Set bucket, container, or path defaults

Enter bucket or container name, optional prefix or folder roots, and region or endpoint URL for S3-compatible stores. For Graph-backed connectors, select the drive or site context the UI requests.
3

Attach cloud or protocol credentials

Link AWS, Azure, GCP, or password/key credentials per the tabs below. Scope IAM or RBAC to the smallest prefix or container the pipeline needs.
4

Confirm encryption and TLS

For object stores, align with your cloud default (SSE-S3, SSE-KMS, customer-managed keys). For SFTP, prefer key-based auth and modern ciphers.
5

Test and attach to pipelines

Run Test connection, then select this connection in file source or destination nodes. Use separate connections per environment (dev-, prod-) to avoid accidental writes.

Authentication patterns

Use IAM user keys only when your policy requires static keys; prefer IAM roles for EKS, EC2, or cross-account assume role if Planasonix runs in AWS.For buckets in another account, use bucket policies that trust the Planasonix role and scope s3:GetObject, s3:PutObject, and s3:ListBucket to prefixes—not entire buckets unless necessary.

Layout and naming

Organize prefixes by source system, date, or pipeline run ID so you can partition incremental loads and apply lifecycle rules without scanning entire buckets. If you write back to storage, use a dedicated export prefix separate from raw landing data.
When the same logical dataset arrives from multiple regions, create one connection per region or bucket to keep latency and data residency boundaries explicit in the UI.

Data warehouses

Load staged files into Snowflake, BigQuery, or similar.

Streaming platforms

When continuous ingestion replaces batch file drops.

Credentials management

Storing and rotating cloud keys and SFTP secrets.

Connections overview

How file connections fit the broader connection model.