Redshift vs BigQuery vs Synapse — Choosing a Cloud Data Warehouse
Amazon Redshift, Google BigQuery, and Azure Synapse are the three dominant cloud data warehouses. Choosing between them is less about which is technically superior and more about which cloud your organization is on and what workload you are running.
Architecture differences
Redshift: cluster-based MPP (Massively Parallel Processing). You provision a cluster of nodes, data is distributed across them, and queries execute in parallel. You pay for the cluster whether it is running queries or idle.
BigQuery: serverless. No cluster to provision. Google manages all compute automatically. You pay per query (per terabyte scanned) or with flat-rate reservations. Scales to petabytes automatically.
Synapse Analytics: hybrid. Dedicated SQL pools (cluster-based, like Redshift) and Serverless SQL pools (query-on-demand, like BigQuery). You choose based on workload pattern.
Performance and cost patterns
BigQuery excels at unpredictable, variable workloads. No cluster to right-size. A query that needs 1000 slots gets them automatically. Cost is directly proportional to data scanned — use partitioning and clustering to minimize scanned bytes.
Redshift excels at steady, predictable workloads with consistent concurrency. A properly provisioned Redshift cluster with good distribution keys outperforms BigQuery on latency for repetitive dashboard queries.
Synapse serverless is cost-effective for ad-hoc exploration over ADLS data. Synapse dedicated pools suit consistent BI workloads.
Ecosystem integration
Redshift: tightest integration with AWS services — S3, Glue, Lake Formation, Kinesis. Redshift Spectrum queries S3 directly without loading. Deep AWS IAM integration.
BigQuery: first-class citizen in GCP. Looker Studio connects natively. Dataflow outputs directly to BigQuery. BigQuery ML runs models inside the warehouse using SQL.
Synapse: native Power BI integration (one click from Synapse workspace). Direct access to ADLS Gen2 Delta Lake tables via external tables. Microsoft Fabric builds on top of Synapse capabilities.
Which should you learn?
Learn the one that matches your target job market:
Targeting Azure-heavy enterprise jobs: Synapse Analytics
Targeting AWS roles: Redshift
Targeting GCP or analytics engineering roles: BigQuery
Conceptually, all three are SQL-based MPP warehouses. If you understand one deeply — partitioning, distribution keys, query optimization — you can pick up the others in a week.