StreamFlows

Extract, transform, and load.
Done well.

End-to-end extraction, transformation, and loading into your analytics warehouse — with dbt-powered transforms, automated scheduling, resumable syncs, and full operational visibility across all your sources.

Everything you need, nothing you don't

A focused feature set built for reliability over feature count.

Multi-source extraction

Connect to Salesforce, Shopify, Google Ads, Stripe, and more. Unified connector interface with automatic schema discovery.

Resumable batch syncing

Checkpoint bookmarks per batch. If a sync fails, it picks up where it left off. No duplicate data, no missed rows.

Operational visibility

Structured logging with correlation IDs across every run. See exactly what happened, when, and why — down to the stream level.

Automatic schema discovery

Detect tables, columns, primary keys, and data types automatically. No manual configuration for standard sources.

Encrypted credentials

All connector credentials are encrypted at rest with AES-256-GCM. OAuth tokens are refreshed automatically before each sync.

Incremental syncing

Track cursor positions and high-water marks to sync only new or changed data. Minimize warehouse costs and sync time.

Field mapping

Control which fields sync, rename columns, and map source types to destination types with per-pipeline overrides.

Destination auto-provisioning

Tables are created and updated automatically in your destination warehouse. Schema changes are detected and applied without manual intervention.

Scheduling & orchestration

Cron-based scheduling with deduplication. Manual runs, backfills with date ranges, and automatic retry on transient failures.

Observability & Alerts

Live visibility into every sync with actionable alerts when something needs attention.

Ease of Use

Simple setup, intuitive interface. No code required to configure and run pipelines.

Extensibility

Open connector framework — build custom integrations when your use case demands it.

Data Transformations

Define transforms with dbt alongside your pipelines. Model and shape your data with SQL-based logic — clean, tested, and version-controlled.

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AI-Assisted Workflows

Early access

AI workflows are rolling out for pipeline setup, failure diagnostics, schema management, and anomaly detection. Designed to make pipelines easier to configure and faster to debug.

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How data flows

A clean separation between control plane and data plane.

Sources
Salesforce logo
Salesforce
HubSpot logo
HubSpot
Google Ads logo
Google Ads
Facebook Ads logo
Facebook Ads
Google Analytics logo
Google Analytics
Shopify logo
Shopify
StreamFlows
Extract
Schedule
Checkpoint
Load
Destinations
PostgreSQL logo
PostgreSQL
Amazon Redshift logo
Amazon Redshift
Google BigQuery logo
Google BigQuery
Snowflake logo
Snowflake
Databricks logo
Databricks

What happens during a sync

Configure
Schedule
Extract
Stage
Load
Verify

Built for these use cases

Common patterns where StreamFlows replaces fragile scripts and manual exports.

Analytics consolidation

Bring data from multiple sources into a single warehouse for unified reporting and cross-source queries.

Ad performance reporting

Sync Google Ads and Facebook Ads data alongside revenue to calculate true ROAS and build attribution models.

Marketing analytics

Combine HubSpot email data, Marketo campaigns, and ad metrics for a complete view of customer engagement.

Data warehouse migration

Move data between warehouses with automatic schema discovery, field mapping, and incremental syncs.

Ready to simplify your data pipelines?

Set up your first sync in minutes. No complex configuration required.