Google Cloud Partner
Move your data warehouse off Amazon Redshift and onto Google BigQuery, schema, data, SQL, pipelines and BI connections intact. A fully serverless analytics platform with no node management, built-in ML and Gemini, delivered with zero data loss.
Yes, you can migrate from Redshift to BigQuery. Codimite, a Google Cloud Partner, moves your Amazon Redshift schema, table data, SQL workloads, pipelines and BI connections into Google BigQuery using the BigQuery Migration Service, which includes a managed Redshift data-transfer connector and Redshift-to-GoogleSQL translation. The result is a fully serverless warehouse with no cluster sizing, built-in BigQuery ML and Gemini, migrated with a phased, zero-data-loss cutover. Redshift-to-BigQuery feasibility is HIGH.
Why migrate
BigQuery removes Redshift's node-type and cluster-resize decisions; you don't provision or scale compute by hand.
Storage and query compute scale and bill independently, so concurrency grows without resizing clusters and cold data stays cheap.
BigQuery ML trains models in SQL and Gemini-assisted analytics adds natural-language querying, no separate ML platform or data export.
Stream events directly into BigQuery for real-time analytics.
On-demand (per-byte-scanned) or flat-rate/capacity pricing matches cost to workload.
No vacuum/analyze, distribution-key or sort-key tuning to keep performance up.
What we migrate
| Redshift object | Migrates to BigQuery | Notes |
|---|---|---|
| Schemas & tables | Datasets & tables | DDL mapped to GoogleSQL types; dist/sort keys to partition/cluster |
| Table data & history | BigQuery table data | Managed Redshift transfer + incremental sync |
| SQL queries & stored logic | GoogleSQL | Translated via BigQuery Migration Service SQL translator |
| ETL / ELT pipelines | Dataflow / Dataform / partner tools | Re-pointed; dbt models re-targeted to BigQuery |
| BI connections | Looker / Tableau / Power BI on BigQuery | Connectors re-pointed, dashboards revalidated |
| Roles & grants | IAM & dataset/column access | Mapped to Google Cloud IAM policies |
SQL fidelity and edge-case function coverage are confirmed during assessment and validated row-by-row.
Our process
We audit your Redshift clusters, schemas, data volume, SQL workloads, pipelines and BI dependencies, and confirm what's portable.
We map Redshift schemas and data types to BigQuery datasets and GoogleSQL types, translating distribution/sort keys to partitioning and clustering.
The BigQuery Migration Service SQL translator converts Redshift SQL to GoogleSQL; engineers remediate edge cases.
The managed Redshift transfer moves historical data, with incremental sync keeping Redshift live in parallel.
Row counts, checksums and query-result parity confirm BigQuery matches the Redshift source.
Partitioning, clustering, materialized views and pricing model tuned to cut query cost and latency.
Why Codimite
Data & analytics migrations are a core practice, delivered as a Google Cloud Partner with 85+ Google Certified Specialists: the managed Redshift transfer plus automated SQL translation, expert remediation where automation falls short, and row-by-row proof that BigQuery matches your source.
Get a QuoteGoogle Cloud Partner. Data & analytics migrations are a core practice, with 85+ Google Certified Specialists.
BigQuery Migration Service expertise. We run the managed Redshift transfer plus automated SQL translation, then remediate what automation can't.
Data-integrity verification. Reconciliation reports prove row counts and query results match source.
Cost optimization built in. Partitioning, clustering and pricing tuning so BigQuery runs lean from day one.
FAQs
Yes, schema, data, SQL, pipelines and BI connections move into BigQuery via the BigQuery Migration Service and its managed Redshift connector. Feasibility is HIGH for Redshift.
Yes, the BigQuery Data Transfer Service has an Amazon Redshift connector that extracts and loads Redshift data into BigQuery, paired with automated SQL translation.
No hard downtime. Historical loads plus incremental sync keep Redshift live in parallel until each workload is validated on BigQuery.
Days for a focused dataset; four to twelve weeks for large enterprise warehouses, driven by data volume, pipeline count and BI dependencies.
Pricing is scoped to data volume, SQL complexity and pipeline count. Start with a free assessment for a fixed quote.
Still comparing platforms? Read Redshift vs BigQuery: Compared (2026) before you decide.
Codimite, a Google Cloud Partner, migrates your Redshift schema, data, SQL and pipelines to Google BigQuery with zero data loss, row-by-row validation and post-migration cost optimization. Start with a free quote.
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