Cut Your Cloud Database Bill by 30–70% — Without Sacrificing Performance
JusDB engineers analyse your AWS, GCP, and Azure database spend and implement hands-on cost reductions: instance rightsizing, Aurora Serverless evaluation, DynamoDB capacity mode optimisation, reserved instance purchasing, idle resource cleanup, and query-level cost attribution.
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Why Cloud Database Bills Spiral Out of Control
Cloud databases are provisioned by engineers optimising for reliability and speed-of-delivery — not cost. The result: predictable over-provisioning patterns that JusDB finds in almost every audit.
Instance Over-Provisioning
Production RDS instances sized for peak load run at 15–30% average CPU. A db.r5.4xlarge at $0.90/hr needed as a db.r6g.xlarge at $0.24/hr — 4× cost reduction with identical query latency.
Idle Read Replicas
Read replicas provisioned for a feature that was never fully adopted, or for a reporting workload that migrated to a data warehouse. Each replica is 100% of the primary instance cost.
Hot Storage for Cold Data
DynamoDB storing 200M records of which 95% are never queried after 30 days. S3 + DynamoDB TTL reduces storage cost by 70–80% for time-series and event data.
Expensive Query Patterns
A single missing index causing full table scans increases RDS CPU — requiring a larger (more expensive) instance. Fix the query, downsize the instance.
No Reserved Instance Strategy
Running production RDS on On-Demand pricing costs 40–60% more than 1-year reserved instances. Most teams never purchase reservations because 'we might change things'.
Oversized Dev/Test Environments
Dev and staging databases running 24/7 at production size. Aurora Serverless v2, scheduled start/stop, or smaller instance families cut non-production costs by 50–80%.
Platform-Specific Cost Optimisations
Amazon AWS
- RDS instance rightsizing (Graviton2/3 migration)
- Aurora Serverless v2 for variable workloads
- RDS Proxy evaluation vs self-managed PgBouncer
- Reserved Instance 1/3-year purchasing strategy
- DynamoDB: on-demand vs provisioned, GSI audit, TTL
- ElastiCache node rightsizing and eviction policy tuning
- S3 Glacier for database backup archival
Google Cloud (GCP)
- Cloud SQL instance rightsizing (E2 vs N2 vs N2D)
- Committed Use Discounts (1-year and 3-year)
- Cloud Spanner: request unit optimisation, split load
- Bigtable node count vs storage cost tradeoff
- Firestore document design for read/write cost reduction
- Dev/test instance scheduling (stop overnight/weekends)
Microsoft Azure
- Azure Database for PostgreSQL/MySQL tier selection
- Azure SQL Hyperscale vs General Purpose evaluation
- Azure Hybrid Benefit for SQL Server licensing
- Reserved capacity pricing for 1/3-year terms
- Cosmos DB RU/s provisioning vs serverless mode
- Azure Cache for Redis tier rightsizing
Real Savings Examples
Representative results from JusDB cost optimisation engagements.
Amazon RDS MySQL
Downsized db.r5.4xlarge to db.r6g.2xlarge + query optimisation reduced CPU from 85% to 28%
Before
$8,400/mo
After
$3,200/mo
Amazon Aurora PostgreSQL
Migrated dev/test clusters to Aurora Serverless v2, eliminated 3 idle read replicas
Before
$12,600/mo
After
$5,800/mo
Amazon DynamoDB
Switched from provisioned to on-demand, added TTL for 120M stale records, optimised GSI usage
Before
$4,200/mo
After
$1,400/mo
GCP Cloud SQL
Committed use discounts, 1-year for production, rightsized staging environments to shared-core
Before
$6,100/mo
After
$3,500/mo
Frequently Asked Questions
Find out how much you can save
JusDB engineers provide a free 1-hour cost audit with specific savings estimates before any engagement starts. No obligation.