BigQuery vs Redshift vs Synapse: Pricing Benchmark Comparison

Introduction: The Three Hyperscaler Data Warehouses

BigQuery, Redshift, and Azure Synapse represent the dominant trio of cloud-native data warehouse platforms. Each is deeply embedded within its respective hyperscaler ecosystem—Google Cloud, Amazon Web Services, and Microsoft Azure—giving them structural advantages in integration, data transfer costs, and compute optimization.

But pricing for these platforms is complex. On-demand rates tell only part of the story. Committed discounts, bundled deals, reserved capacity, and hidden egress fees often account for 30-40% variance between list price and actual enterprise spend. For procurement teams evaluating multi-million dollar commitments, getting the comparison right is critical.

This benchmark compares pricing models, discount structures, and total cost of ownership across all three platforms at scale. We'll address the question that procurement teams actually ask: "What will we pay, and what leverage do we have to negotiate?"

For a deeper dive into data platform economics across the entire landscape, read our Data Platform Pricing benchmark guide, which covers pricing strategy for 15+ data platforms including snowflake, databricks, and redshift competitor analysis.

BigQuery Pricing Model: On-Demand, Editions, and Slots

Google BigQuery offers three distinct pricing paths, each designed for different usage patterns and organizational maturity levels.

On-Demand Pricing

BigQuery's on-demand model charges $6.25 per terabyte (TB) of data scanned, not stored. This is the default and most flexible option—there's no upfront commitment, no minimum spend, and scaling is automatic. For organizations that run unpredictable workloads, this eliminates procurement friction.

However, on-demand pricing scales poorly. An organization scanning 1,000 TB per month pays $6,250. At 5,000 TB per month, costs hit $31,250. The lack of volume discounts means large-scale users subsidize smaller ones.

BigQuery Editions: Standard, Enterprise, Enterprise Plus

Google introduced Editions in 2023 as a middle ground between on-demand and committed capacity. Each edition bundles compute, storage, and analytics into fixed monthly tiers:

Standard Edition: $0.04 per GB stored + $0.004 per GB analyzed. Targets teams just starting with analytics. No real competitive advantage for enterprise buyers.

Enterprise Edition: $2,000/month flat for compute + storage charges. Includes multi-region support, increased API quotas, and priority support. Query costs drop to $5.25/TB scanned (16% savings vs on-demand).

Enterprise Plus Edition: $4,000/month flat for compute + storage charges. Adds advanced security features, dual-region replication, and access to cutting-edge AI/ML features. Query costs drop to $4.69/TB (25% savings vs on-demand).

For organizations processing 500-2,000 TB monthly, Editions provide 15-25% cost savings without long-term commitment. For larger volumes, reserved capacity (slots) becomes more attractive.

Slot Pricing and Committed Use Discounts

BigQuery's slot model reserves compute capacity at a fixed monthly or annual rate. One slot provides 100 slots of query capacity per month. Pricing starts at $0.04 per slot-hour (approximately $2,000/month for one annual slot), scaling to $0.048 per slot-hour on-demand.

Committed discounts apply:

• 1-Year Commitment: $2,000/month per slot (25% discount)
• 3-Year Commitment: $1,700/month per slot (37.5% discount)

At scale, this model is powerful. A mid-market company processing 10,000 TB monthly (10 slots needed) pays approximately $240,000 annually with a 3-year commitment—roughly $20/TB, compared to $62.50/TB on-demand.

Redshift Pricing Model: Provisioned Clusters vs Serverless

AWS Redshift offers two pricing models, reflecting the shift toward serverless architectures while maintaining backward compatibility with legacy provisioned deployments.

Provisioned Redshift Clusters

Traditional Redshift pricing is node-based. You provision a cluster of compute nodes; AWS charges per node-hour regardless of utilization. Three node types dominate enterprise deployments:

RA3.XLPLUS: $3.26 per node-hour (approximately $2,332/month per node, 24/7). Good for workloads under 500 TB. Includes managed storage.

RA3.4XLARGE: $13.04 per node-hour (approximately $9,329/month per node). Recommended for 500-2,000 TB clusters. Four times the compute of XLPLUS.

RA3.16XLARGE: $52.16 per node-hour (approximately $37,315/month per node). For data warehouses exceeding 2,000 TB.

A four-node RA3.4XLARGE cluster costs approximately $37,316/month ($447,792 annually). Comparable organizations on BigQuery slots pay $20,000-40,000 monthly for equivalent capacity, making Redshift generally more expensive for pure compute costs.

Redshift Serverless

Redshift Serverless abstracts away node management. Instead, you pay for "Redshift Processing Units" (RPUs) on a per-second basis: $0.375 per RPU-hour, roughly $2,700/month per RPU with 24/7 utilization.

Serverless removes operational overhead and right-sizing complexity. However, most organizations find provisioned clusters 15-20% cheaper at equivalent capacity due to committed discounts on traditional Redshift.

Reserved Instance Discounts

AWS offers Reserved Instances (RIs) for provisioned Redshift:

• 1-Year Upfront: 25% discount
• 3-Year Upfront: 45% discount

A four-node cluster at 45% discount costs approximately $246,285 annually—a meaningful saving, but still higher than comparable BigQuery commitments for the same workload.

Synapse Analytics Pricing: Dedicated SQL Pools vs Serverless

Azure Synapse Analytics offers pricing similar in structure to Redshift: dedicated (provisioned) and serverless tiers, but with Microsoft's volume licensing discount ecosystem.

Dedicated SQL Pools

Synapse's dedicated pools are priced per Data Warehouse Unit (DWU). One DWU combines compute, memory, and I/O in a fixed bundle. Pricing starts at approximately $1.38 per DWU-hour for DW500c, scaling to $21.12 per DWU-hour for DW30000c.

A typical mid-market deployment (DW3000) costs approximately $1,656/month on-demand. With Azure Reserved Instances:

• 1-Year RI: 31% discount (~$1,143/month)
• 3-Year RI: 62% discount (~$629/month)

Synapse's 3-year RI pricing is competitive with BigQuery Editions for mid-market workloads (500-2,000 TB), but for very large deployments (10,000+ TB), BigQuery slots generally undercut both Redshift and Synapse.

Serverless SQL Pools

Synapse Serverless charges $5 per TB scanned—identical to BigQuery Enterprise Edition ($5.25/TB). However, Synapse Serverless lacks reserved capacity discounts, making it effectively more expensive than BigQuery for committed workloads.

Head-to-Head Total Cost of Ownership at $500K Annual Spend

To directly compare platforms, let's model a $500,000 annual data warehouse budget and calculate equivalent capacity:

At $500K total budget, Synapse comes in lowest, but only if your organization is already Microsoft-committed. If you're platform-agnostic, BigQuery's pricing is most predictable, while Redshift offers leverage if AWS is your strategic provider.

Enterprise Discount Availability by Platform

BigQuery Negotiated Discounts: Limited beyond published Editions and Slots. Google's approach is less discount-oriented than competitors. However, customers who commit to long-term slots (3-year terms) can negotiate 5-10% bundled discounts on top of listed prices. Organizations consolidating analytics workloads across multiple projects sometimes secure package pricing.

Redshift Negotiated Discounts: AWS Enterprise Discount Program (EDP) is widely available to organizations spending $100K+ annually on AWS. Discounts typically range from 20-40% and stack on top of Reserved Instance pricing. At very large scale ($5M+ annual AWS spend), discounts can reach 50%.

Synapse Negotiated Discounts: Microsoft's MACC (Azure Consumption Commitment) is the primary negotiation vehicle. Organizations committing to annual Azure spend thresholds receive percentage discounts on consumption. MACC discounts scale from 10% at $50K commitment to 40%+ at $500K+ commitment. This makes Synapse highly competitive within Microsoft shops.

Total Cost Across Realistic Query Volumes

Let's model three common enterprise scenarios to show total cost including compute, storage, and negotiated discounts:

The data shows clear patterns:

BigQuery wins at 200TB+ monthly workloads, especially with 3-year slots. Its per-query pricing scales smoothly without node constraints.

Redshift becomes competitive with deep EDP discounts, particularly for AWS-native organizations. The 20-40% EDP discount can shift breakeven points significantly.

Synapse dominates within Microsoft ecosystems due to MACC bundling. Organizations running SQL Server, Dynamics 365, and Office 365 can achieve Synapse costs 30-40% below standalone pricing.

Data Egress and Cross-Cloud Costs: The Hidden Differentiator

Query processing costs tell only half the story. Data egress charges can add 10-30% to total cost, depending on architecture.

BigQuery Egress Costs

BigQuery charges $0.12 per GB for data egress to the internet (outside Google Cloud). Intra-region transfers are free; cross-region transfers within Google Cloud are $0.01/GB. For organizations moving 100 TB monthly out of BigQuery (common in multi-cloud architectures), egress adds $12,000/month.

Redshift Egress Costs

AWS charges $0.02 per GB for inter-regional data transfer and $0.02 per GB for data transfer to the internet. Intra-region transfers between Redshift and EC2 are free, but cross-region transfers to another AWS region cost $0.02/GB. For 100 TB monthly, egress is approximately $2,000/month—significantly cheaper than BigQuery if you're shipping data across regions.

Synapse Egress Costs

Azure charges $0.02 per GB for egress within the same region, $0.04 per GB for cross-region egress, and $0.15 per GB for egress to the internet. Synapse egress is cheaper than BigQuery but more expensive than Redshift for cross-region transfers.

For organizations building data pipelines that frequently move data between cloud platforms or to on-premises systems, Redshift's low egress costs provide meaningful leverage in negotiations. BigQuery's premium egress pricing often surprises procurement teams and should factor into total cost models.

Negotiation Angles by Platform

BigQuery Negotiation Strategy: Google's pricing is relatively fixed. Negotiation room exists primarily through bundled deals (combining BigQuery with Google Cloud Storage, Looker, Vertex AI, etc.). Position your RFP around multi-year slots with bundle discounts. Emphasize predictability and lack of node-tuning overhead. Data egress is the leverage point—if you're moving large volumes out of BigQuery, you have room to negotiate egress cost relief.

Redshift Negotiation Strategy: AWS EDP discounts are negotiable, especially if your organization has committed AWS spend roadmaps. Position Redshift as part of a broader AWS commitment (EC2, RDS, Lambda, etc.). Bundle Redshift into a holistic AWS pricing discussion. At scale, AWS will often discount Redshift more aggressively than other services to lock in your analytics spend. Request volume discounts on Reserved Instance purchases and explore multi-year commitments.

Synapse Negotiation Strategy: Frame Synapse as part of a Microsoft platform strategy. Link it to existing SQL Server, Power BI, and Office 365 commitments. Microsoft's bundling mindset means Synapse pricing is most flexible when negotiated as part of a broader MACC agreement. If you're already in a MACC commitment, pushing additional Synapse capacity into it is often cheaper than negotiating standalone discounts.

FAQ: Common Procurement Questions

1. Should we commit to 3-year slots/RIs, or stay flexible with on-demand?

For workloads you expect to maintain at stable levels for 18+ months, 3-year commitments offer 30-40% savings and should be your default. However, avoid over-committing. Size commitments to your baseline stable workload, then handle seasonal spikes with on-demand overages. This hybrid approach optimizes both cost and flexibility.

2. Can we negotiate discounts beyond published pricing?

Yes. BigQuery offers limited negotiation but responds to bundle deals. Redshift has broad EDP discounts (20-40%). Synapse is highly negotiable within MACC frameworks. Always ask for "not published" discounts—cloud vendors have flexibility beyond list prices.

3. How does total cost change if we increase query volume mid-contract?

On BigQuery slots, adding capacity is seamless—you simply add slots at the committed rate. On Redshift, adding nodes mid-contract to a Reserved Instance commitment requires new RIs at current rates (no retroactive discounts). Synapse follows similar rules. Factor growth expectations into initial sizing.

4. What happens to our pricing if we consolidate multiple workloads onto one platform?

Consolidation often triggers volume discounts. BigQuery might offer 5-10% bundle relief. Redshift's EDP becomes more generous (larger spend threshold = larger discount). Synapse benefits most—consolidation justifies larger MACC commitments, triggering 30-40%+ discounts. Use consolidation as a negotiation lever.

5. Are there hidden costs we should model?

Yes. Data egress (10-30% of costs in multi-cloud setups), data transfer for backups, and BI tool licensing (Looker for BigQuery, QuickSight for Redshift, Power BI for Synapse) add meaningful expense. Model these as 15-25% adders to platform costs in your TCO.

Conclusion: Choosing Your Platform Based on Cost and Leverage

There is no universally cheapest option. Your choice depends on ecosystem, negotiation leverage, and workload characteristics:

Choose BigQuery if: You need predictable, transparent pricing; you're platform-agnostic; you want to avoid node-sizing complexity; or you're processing 200+ TB monthly and can commit to 3-year slots. Best-case scenario: $20-30/TB at scale with negotiated bundle discounts.

Choose Redshift if: You're committed to AWS; you can leverage EDP discounts; you need aggressive egress cost control; or you're already running significant workloads on EC2 and RDS. Best-case scenario: $15-25/TB at scale with EDP + RI discounts.

Choose Synapse if: You're a Microsoft shop; you can fold Synapse into MACC; you're already paying for SQL Server, Dynamics, and Power BI; or you need tightly integrated BI tools. Best-case scenario: $8-15/TB at scale within a bundled Microsoft agreement.

Start with a 12-month pilot on your primary platform, lock in a modest committed capacity, and measure your actual cost per TB. Use that data to negotiate aggressively. Don't let list prices guide your decision—they rarely reflect what enterprises actually pay.