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AWS MySQL Showdown:
RDS vs. Aurora vs. Serverless
Presented by
Maha Lakshmi G
Mydbops
Feb 21, 2025
Mydbops MyWebinar Edition- 41
Agenda
❏ Abstract
❏ Architecture
❏ Storage Design
❏ High Availability Mechanisms
❏ Performance Considerations
❏ Cost-Benefit Analysis
❏ Conclusion
Abstract
❏ AWS offers RDS MySQL, Multi-AZ RDS Cluster, and
Aurora MySQL for scalable and high-availability database solutions.
❏ Each service differs in architecture, replication methods, failover
mechanisms, and cost efficiency.
❏ This webinar will compare storage design, high availability, and
performance to help organizations choose the right solution.
Architecture and
Storage Design
Architecture- AWS RDS MySQL
❏ Single-AZ Deployment – Single primary instance in one AZ.
P
Single Primary
Read + Write
Architecture- AWS RDS MySQL
❏ Multi-AZ Deployment – Standby instance in another AZ
(synchronous replication, automatic failover).
Architecture- AWS RDS MySQL
❏ Multi-AZ RDS Cluster– One writer DB instance and two reader DB
instances across three AZs. (semi- synchronous replication)
Storage Design- AWS RDS MySQL
❏ AWS RDS MySQL Storage Options
Storage Type Storage Size Provisioned IOPS Max Throughput
io2 100 GiB – 65,536 GiB 1,000 – 256,000 IOPS 16,000 MiB/s
io1
100 – 399 GiB 1,000 – 19,950 IOPS 500 MiB/s
400 – 65,536 GiB 1,000 – 256,000 IOPS 4,000 MiB/s
gp3
20 – 399 GiB Baseline: 3,000 IOPS 125 MiB/s
400 – 65,536 GiB 12,000 – 64,000 IOPS 500 – 4,000 MiB/s
gp2
(not recommended)
5 – 399 GiB 100 – 1,197 IOPS 128 – 250 MiB/s
400 – 1,335 GiB 1,200 – 4,005 IOPS 512 – 1,000 MiB/s
1,336 – 3,999 GiB 4,008 – 11,997 IOPS 1,000 MiB/s
4,000 – 65,536 GiB 12,000 – 64,000 IOPS 1,000 MiB/s
Architecture- AWS Aurora MySQL
❏ Cluster-Based Design – One primary (writer) DB instance and up to
15 reader DB instances sharing the same storage
❏ Shared Storage – A single, SSD-backed cluster volume replicated
across three AZs for durability. Automatically expands up to 128 TiB
based on data
Storage Design- AWS Aurora MySQL
Architecture- Aurora Serverless
❏ Auto-Scaling Compute
❏ SSD-backed storage automatically scales up to 128 TiB.
❏ Maintains six copies of data across three AZs for reliability.
❏ Instances start/stop dynamically without affecting stored data.
❏ Pauses compute when idle and restarts on demand to reduce costs.
Storage Design- Aurora Serverless
High Availability
Mechanisms
High Availability Mechanisms- AWS RDS MySQL
❏ Single-AZ:
● No automatic failover; recovery requires manual intervention.
❏ Multi-AZ (Standby Mode):
● Automatic failover (~60-120 seconds)
● Standby cannot process read requests until promoted to primary.
❏ RDS Multi-AZ Cluster:
● Faster failover (~35-50 seconds)
High Availability Mechanisms- AWS Aurora MySQL
❏ Amazon Aurora:
● Automatic failover to a reader instance within ~30 seconds.
● Aurora promotes the most up-to-date reader instance to primary,
automatically updating the cluster endpoint.
❏ Aurora Serverless
● If an instance fails, Aurora Serverless provisions a new instance
automatically and reroutes traffic with minimal disruption.
Replication
Mechanisms
Replication Mechanisms
❏ RDS MySQL (Single-AZ) → No replication; single instance. Supports
up to 5 read replicas using binlog-based asynchronous replication.
❏ RDS MySQL (Multi-AZ - One Standby) → Uses synchronous physical
replication to a passive standby in another AZ (no read traffic).
❏ Multi-AZ RDS Cluster → Uses semi-synchronous physical replication
to 2 standbys, which serve read traffic. Also supports binlog-based
async read replicas.
Replication Mechanisms
❏ Aurora MySQL → Uses storage-based replication with 6 copies
across 3 AZs, eliminating the need for binlog-based replication.
Aurora Replicas read directly from shared storage, supporting up to
15 replicas with minimal lag.
❏ Aurora Serverless → Uses the same Aurora storage-based
replication but automatically scales compute based on demand.
Performance
Considerations
Performance Considerations- AWS RDS MySQL
❏ Single-AZ and Multi-AZ (Standby Mode):
● Storage Options:
SSD-backed GP3/GP2 (cost-effective)
IO1 (up to 256,000 IOPS for OLTP).
● Scalability: Expand storage on-the-fly with zero downtime.
● Optimized Writes: 2x faster write throughput.
● Optimized Reads: Up to 50% faster query performance.
● Read Replication: Uses asynchronous replication with Read
Replicas for scaling read operations.
Performance Considerations- AWS RDS Multi-AZ Cluster
❏ AWS RDS Multi-AZ Cluster:
● Faster Transactions: Up to three active DB instances with shared
storage.
● Lower Latency: Parallel writes across AZs reduce replication lag.
● Read Scaling: Read replicas handle queries, easing primary load.
● Quick Failover: Faster recovery (~35-50s) than Multi-AZ standby.
● Replication Mechanism: Uses synchronous replication across
instances in different AZs for improved durability and availability.
Performance Considerations- AWS Aurora MySQL
❏ Amazon Aurora:
● Highly Durable Storage: Data is replicated six times across three AZs.
● High Performance: Supports up to 200,000 write IOPS
with low-latency replication.
● Read Scalability: Up to 15 read replicas with near-instant replication.
● Optimized Queries: Parallel execution enhances analytical workloads.
● Auto-Scaling Storage: Expands automatically up to 128 TiB without
downtime.
Performance Considerations- AWS Aurora MySQL
❏ Aurora Serverless:
● Dynamic Compute Scaling: Adjusts capacity instantly based on demand.
● Startup Latency: Initial activation may cause slight delay.
● Cost-Efficient: Pay only for actual usage, preventing over-provisioning.
● Reliable Storage: Utilizes Aurora's six-way replicated storage across AZs.
● Ideal for Variable Workloads: Best suited for unpredictable database traffic.
● Replication Mechanism: Uses storage-level replication across
multiple AZs, just like standard Aurora, ensuring high durability and
availability.
Cost-Benefit Analysis
Cost-Benefit Analysis- AWS RDS MySQL
❏ Pricing Models:
● On-Demand Instances: Pay for compute capacity by the hour with no
long-term commitments. Suitable for applications with unpredictable
workloads.
● Reserved Instances: Commit to a one- or three-year term to receive
significant discounts, up to 66% over On-Demand rates.
Ideal for steady-state workloads.
Cost-Benefit Analysis- AWS Aurora MySQL
❏ Pricing Models:
● Aurora Standard: Pay for database instances, storage, and I/O
operations. Suitable for applications with low to moderate I/O usage.
● Aurora I/O-Optimized: Ideal for I/O-intensive applications, offering up
to 40% cost savings when I/O spend exceeds 25% of total Aurora
database spend.
Cost-Benefit Analysis- AWS Aurora Serverless
❏ Pricing Models:
● On-Demand Scaling: Automatically adjusts compute capacity based on
application demand, ideal for variable or unpredictable workloads.
● Cost Efficiency: Charges are based on actual usage,
preventing costs associated with over-provisioning.
Key Takeaways
AWS MySQL Showdown: RDS vs. Aurora vs. Serverless
Feature RDS MySQL RDS Multi-AZ
Cluster
Aurora MySQL Aurora
Serverless
Architecture Single/Multi-AZ,
Standby-based
Multi-AZ, multiple
active DBs
Cluster-based,
shared storage
Auto-scaling,
ephemeral instances
Storage SSD-backed,
fixed-size
Shared SSD-backed,
auto-expands
Shared SSD-backed,
auto-expands
Shared SSD-backed,
auto-expands
High Availability Multi-AZ failover
(60-120s)
Faster failover
(~35-50s)
Fast failover (~30s) Auto-provisions new
instance
Performance Read replicas for
scaling
Parallel writes, lower
latency
15 replicas, parallel
queries
Scales compute
dynamically
Cost Model On-Demand &
Reserved
On-Demand &
Reserved
Standard &
I/O-Optimized
Pay-per-use, no
over-provisioning
Any Questions?
Consulting
Services
Consulting
Services
Connect with us !
Reach us at : info@mydbops.com
Thank you!
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AWS MySQL Showdown - RDS vs RDS Multi AZ vs Aurora vs Serverless - Mydbops Webinar 41

  • 1. AWS MySQL Showdown: RDS vs. Aurora vs. Serverless Presented by Maha Lakshmi G Mydbops Feb 21, 2025 Mydbops MyWebinar Edition- 41
  • 2. Agenda ❏ Abstract ❏ Architecture ❏ Storage Design ❏ High Availability Mechanisms ❏ Performance Considerations ❏ Cost-Benefit Analysis ❏ Conclusion
  • 3. Abstract ❏ AWS offers RDS MySQL, Multi-AZ RDS Cluster, and Aurora MySQL for scalable and high-availability database solutions. ❏ Each service differs in architecture, replication methods, failover mechanisms, and cost efficiency. ❏ This webinar will compare storage design, high availability, and performance to help organizations choose the right solution.
  • 5. Architecture- AWS RDS MySQL ❏ Single-AZ Deployment – Single primary instance in one AZ. P Single Primary Read + Write
  • 6. Architecture- AWS RDS MySQL ❏ Multi-AZ Deployment – Standby instance in another AZ (synchronous replication, automatic failover).
  • 7. Architecture- AWS RDS MySQL ❏ Multi-AZ RDS Cluster– One writer DB instance and two reader DB instances across three AZs. (semi- synchronous replication)
  • 8. Storage Design- AWS RDS MySQL ❏ AWS RDS MySQL Storage Options Storage Type Storage Size Provisioned IOPS Max Throughput io2 100 GiB – 65,536 GiB 1,000 – 256,000 IOPS 16,000 MiB/s io1 100 – 399 GiB 1,000 – 19,950 IOPS 500 MiB/s 400 – 65,536 GiB 1,000 – 256,000 IOPS 4,000 MiB/s gp3 20 – 399 GiB Baseline: 3,000 IOPS 125 MiB/s 400 – 65,536 GiB 12,000 – 64,000 IOPS 500 – 4,000 MiB/s gp2 (not recommended) 5 – 399 GiB 100 – 1,197 IOPS 128 – 250 MiB/s 400 – 1,335 GiB 1,200 – 4,005 IOPS 512 – 1,000 MiB/s 1,336 – 3,999 GiB 4,008 – 11,997 IOPS 1,000 MiB/s 4,000 – 65,536 GiB 12,000 – 64,000 IOPS 1,000 MiB/s
  • 9. Architecture- AWS Aurora MySQL ❏ Cluster-Based Design – One primary (writer) DB instance and up to 15 reader DB instances sharing the same storage ❏ Shared Storage – A single, SSD-backed cluster volume replicated across three AZs for durability. Automatically expands up to 128 TiB based on data
  • 10. Storage Design- AWS Aurora MySQL
  • 11. Architecture- Aurora Serverless ❏ Auto-Scaling Compute ❏ SSD-backed storage automatically scales up to 128 TiB. ❏ Maintains six copies of data across three AZs for reliability. ❏ Instances start/stop dynamically without affecting stored data. ❏ Pauses compute when idle and restarts on demand to reduce costs.
  • 14. High Availability Mechanisms- AWS RDS MySQL ❏ Single-AZ: ● No automatic failover; recovery requires manual intervention. ❏ Multi-AZ (Standby Mode): ● Automatic failover (~60-120 seconds) ● Standby cannot process read requests until promoted to primary. ❏ RDS Multi-AZ Cluster: ● Faster failover (~35-50 seconds)
  • 15. High Availability Mechanisms- AWS Aurora MySQL ❏ Amazon Aurora: ● Automatic failover to a reader instance within ~30 seconds. ● Aurora promotes the most up-to-date reader instance to primary, automatically updating the cluster endpoint. ❏ Aurora Serverless ● If an instance fails, Aurora Serverless provisions a new instance automatically and reroutes traffic with minimal disruption.
  • 17. Replication Mechanisms ❏ RDS MySQL (Single-AZ) → No replication; single instance. Supports up to 5 read replicas using binlog-based asynchronous replication. ❏ RDS MySQL (Multi-AZ - One Standby) → Uses synchronous physical replication to a passive standby in another AZ (no read traffic). ❏ Multi-AZ RDS Cluster → Uses semi-synchronous physical replication to 2 standbys, which serve read traffic. Also supports binlog-based async read replicas.
  • 18. Replication Mechanisms ❏ Aurora MySQL → Uses storage-based replication with 6 copies across 3 AZs, eliminating the need for binlog-based replication. Aurora Replicas read directly from shared storage, supporting up to 15 replicas with minimal lag. ❏ Aurora Serverless → Uses the same Aurora storage-based replication but automatically scales compute based on demand.
  • 20. Performance Considerations- AWS RDS MySQL ❏ Single-AZ and Multi-AZ (Standby Mode): ● Storage Options: SSD-backed GP3/GP2 (cost-effective) IO1 (up to 256,000 IOPS for OLTP). ● Scalability: Expand storage on-the-fly with zero downtime. ● Optimized Writes: 2x faster write throughput. ● Optimized Reads: Up to 50% faster query performance. ● Read Replication: Uses asynchronous replication with Read Replicas for scaling read operations.
  • 21. Performance Considerations- AWS RDS Multi-AZ Cluster ❏ AWS RDS Multi-AZ Cluster: ● Faster Transactions: Up to three active DB instances with shared storage. ● Lower Latency: Parallel writes across AZs reduce replication lag. ● Read Scaling: Read replicas handle queries, easing primary load. ● Quick Failover: Faster recovery (~35-50s) than Multi-AZ standby. ● Replication Mechanism: Uses synchronous replication across instances in different AZs for improved durability and availability.
  • 22. Performance Considerations- AWS Aurora MySQL ❏ Amazon Aurora: ● Highly Durable Storage: Data is replicated six times across three AZs. ● High Performance: Supports up to 200,000 write IOPS with low-latency replication. ● Read Scalability: Up to 15 read replicas with near-instant replication. ● Optimized Queries: Parallel execution enhances analytical workloads. ● Auto-Scaling Storage: Expands automatically up to 128 TiB without downtime.
  • 23. Performance Considerations- AWS Aurora MySQL ❏ Aurora Serverless: ● Dynamic Compute Scaling: Adjusts capacity instantly based on demand. ● Startup Latency: Initial activation may cause slight delay. ● Cost-Efficient: Pay only for actual usage, preventing over-provisioning. ● Reliable Storage: Utilizes Aurora's six-way replicated storage across AZs. ● Ideal for Variable Workloads: Best suited for unpredictable database traffic. ● Replication Mechanism: Uses storage-level replication across multiple AZs, just like standard Aurora, ensuring high durability and availability.
  • 25. Cost-Benefit Analysis- AWS RDS MySQL ❏ Pricing Models: ● On-Demand Instances: Pay for compute capacity by the hour with no long-term commitments. Suitable for applications with unpredictable workloads. ● Reserved Instances: Commit to a one- or three-year term to receive significant discounts, up to 66% over On-Demand rates. Ideal for steady-state workloads.
  • 26. Cost-Benefit Analysis- AWS Aurora MySQL ❏ Pricing Models: ● Aurora Standard: Pay for database instances, storage, and I/O operations. Suitable for applications with low to moderate I/O usage. ● Aurora I/O-Optimized: Ideal for I/O-intensive applications, offering up to 40% cost savings when I/O spend exceeds 25% of total Aurora database spend.
  • 27. Cost-Benefit Analysis- AWS Aurora Serverless ❏ Pricing Models: ● On-Demand Scaling: Automatically adjusts compute capacity based on application demand, ideal for variable or unpredictable workloads. ● Cost Efficiency: Charges are based on actual usage, preventing costs associated with over-provisioning.
  • 29. AWS MySQL Showdown: RDS vs. Aurora vs. Serverless Feature RDS MySQL RDS Multi-AZ Cluster Aurora MySQL Aurora Serverless Architecture Single/Multi-AZ, Standby-based Multi-AZ, multiple active DBs Cluster-based, shared storage Auto-scaling, ephemeral instances Storage SSD-backed, fixed-size Shared SSD-backed, auto-expands Shared SSD-backed, auto-expands Shared SSD-backed, auto-expands High Availability Multi-AZ failover (60-120s) Faster failover (~35-50s) Fast failover (~30s) Auto-provisions new instance Performance Read replicas for scaling Parallel writes, lower latency 15 replicas, parallel queries Scales compute dynamically Cost Model On-Demand & Reserved On-Demand & Reserved Standard & I/O-Optimized Pay-per-use, no over-provisioning