BigQuery DTS: Zero-Code Data Ingestion Gets New Connectors

In the fast-paced digital economy, data is your most critical engine. Yet many enterprises find themselves trapped in a costly paradox—spending over 100 hours a week building and fixing fragile, in-house ETL pipelines or wrestling with unpredictable third-party tools.

Trusted by thousands of customers every single day, BigQuery Data Transfer Service (DTS) eliminates this engineering burden. As a fully managed, zero-code data movement solution, BigQuery DTS automates data ingestion into BigQuery, letting your teams transition from pipeline maintenance to strategic data science in minutes.

Expanding the ecosystem: New connectors and capabilities

We’re rapidly expanding our integration landscape to eliminate data silos across databases, ads, and marketing platforms. Here are the latest additions and enhancements:

Open Lakehouse ingestion

• Direct ingestion into Apache Iceberg managed tables (Preview): Ingest data from Google Cloud Storage, Amazon S3, and Azure Blob Storage directly into Iceberg managed tables. This enables full multi-cloud storage cross-compatibility with other query engines while leveraging BigQuery’s top-tier performance tuning.

Next-gen agentic architecture

• Fully managed remote Model Context Protocol (MCP) Server (Preview): Connect your AI applications and agents to DTS, allowing them to programmatically discover data sources and configure/execute transfers on the user’s behalf.

Enterprise and relational databases (full or incremental transfers)

• Microsoft SQL Server (Preview): Centralize transactional tables, schemas, and operational data directly into your analytical environment in BigQuery.
• PostgreSQL (GA) and MySQL (GA): Automate data delivery and simplify replication of high-volume web and application workloads into your central data warehouse within minutes. Supports on-premise, CloudSQL, and other clouds.

E-commerce and growth marketing

• Shopify (Preview): Automates extraction of granular order histories, inventory logs, and customer profiles.
• Klaviyo (Preview): Extracts detailed email and SMS engagement logs (clicks, sends, opens) to build precise multi-channel lifecycle attributes.
• HubSpot (Preview): Syncs pipeline, contact tracking, and inbound marketing metrics to keep revenue operations aligned.
• Mailchimp (Preview): Automatically moves campaign performance and audience list attributes into your warehouse.

Migration connectors

• Snowflake (GA): Migrate data from Snowflake with incremental transfer, auto schema detection, private connectivity, and support for all three major clouds (Google Cloud, AWS, Azure).

Enhancements to major connectors

• ServiceNow, Salesforce, and Oracle: Enhanced with native incremental update support to speed up large-scale pipeline refreshes for enterprise CRM, ITSM, and financial workflows.

Why choose BigQuery Data Transfer Service?

Moving data across an enterprise architecture shouldn’t require complex compromises between cost, management overhead, and pipeline health. BigQuery DTS delivers unique advantages across three pillars:

1. Unbeatable cost efficiency

• Zero ingestion costs for major sources: No-charge ingestion for all first-party Google sources (except Google Play), including Google Ads, Google Analytics 4, Campaign Manager, YouTube, and Google Cloud Storage. Also free for Amazon S3, Azure Blob Storage, Amazon Redshift, and Teradata.
• Low consumption-based rates for third-party SaaS: Compute fees run less than 6 cents per slot-hour in major regions. Pricing scales with compute footprint, not row volume, so you can efficiently transfer massive data volumes.

2. Frictionless security and native management

Eliminate middlemen servers and external security configurations. BigQuery DTS fully integrates with Cloud IAM. Transfers instantly inherit your destination dataset’s Column-Level Security, Row-Level Security, and Customer-Managed Encryption Keys (CMEK) without extra overhead. Your streams flow securely inside the native Google Cloud perimeter.

3. Industry-leading performance and resilience

When you manage data at enterprise scale, downtime means lost business. BigQuery DTS provides a highly resilient ingestion footprint backed by a strict Google Cloud SLA, delivering a monthly uptime percentage of ≥99.99%. Your analytics, automated pipelines, and operational dashboards update reliably.

Ready to transform your data operations?

Stop letting manual ingestion scripts limit your growth. Join the thousands of companies relying on Google’s native cloud lakehouse data movement architecture to build a modern, scalable data stack.

Try the platform today: Navigate to the BigQuery Data Transfer Service console, pick your connector, and deploy your first automated transfer in just a few clicks!

What connectors should we build next?

We’re constantly expanding our native integration library based on your business needs. What sources are you currently forced to extract manually? Are there specific relational databases, NoSQL engines, or regional SaaS platforms you need to replicate next? Let us know with a feature request via the public issue tracker.

For more on how BigQuery stacks up against other platforms, check out our Google Cloud review and model pricing comparison.

Original announcement published on Google Cloud.