Level Up Your Data Management Game: Unleash Performance in Aurora Limitless
Level Up Your Data Management Game: Unleash Performance in Aurora Limitless
Published Feb 11, 2024
- Aurora is part of Amazon RDS.
- It supports MySQL and PostgreSQL relational databases.
- It offers cost-effectiveness with auto-scaling capabilities.
- It provides simplicity in setup and operation.
- Aurora supports clustering replication.
- Aurora Limitless supports PostgreSQL-compatible Aurora databases.
- It allows scaling beyond the limits of an Aurora database instance.
- It enables horizontal scaling of write throughput for increased storage capacity.
- It ensures transactional consistency by distributing data and query load across multiple Serverless instances.
- Aurora Limitless features auto-scaling, eliminating the need for manual provisioning.
- Additional capacity for writers and readers is provided through the Aurora cluster.
- Distributed query planning and transaction management facilitate transparent scaling complexity.
- Distributed query planning optimizes queries.
- It allows retrieval of data stored across multiple databases.
- It enables optimal parallelization of query execution while maintaining transactional consistency.
- It behaves as a single logical instance, optimizing performance and resource utilization.
Benefits:
- Supports high write throughput and storage beyond a single instance's capabilities.
- Enables horizontal scaling for unpredictable and rapidly growing workloads.
- Automates sharding and replication processes.
- involves coordinating operations across distributed databases.
- ensures data integrity by addressing issues related to parallelized operations, concurrency, replication, and distributed queries.
- coordinates transactions across scaled-out databases, allowing seamless horizontal scaling.
AWS Aurora Limitless Database has two types of tables: Sharded tables & Reference tables.
What are Sharded tables?
- Sharded tables are distributed across multiple database shards.
- Data is split based on designated columns (shard keys) and stored in sharded tables.
- Sharded tables are used for extremely large tables that need to be horizontally partitioned across instances.
- The main benefit of sharded tables is scaling and achieving high throughput.
What are Reference tables?
- Reference tables contain data that is present on every shard.
- They allow join queries to work faster by reducing unnecessary data movement across shards.
- Reference tables are typically used for infrequently modified reference data, such as zip codes.
- Real-time analytics on large datasets.
- High-volume transaction processing.
- Ideal for managing massive datasets and heavy database usage.
Example 1: GSR
- GSR, one of the largest Crypto Market Makers.
- Handles more than 1.1 million trades per day.
- Utilizes Aurora for high performance and availability at a global scale.
Example 2: Magnetic Asia
- Magnetic Asia operates a live streaming events platform called Total Streaming, with up to 50,000 attendees.
- Their virtual ticketing solution, Total Ticketing, relies on Aurora.
- Aurora intelligently scales the database based on workload requirements.