For the eighth consecutive year, Amazon Web Services is named a leader in Gartner’s annual “Magic Quadrant” rankings for the cloud database space. The new rankings, which evaluate the world’s top 20 data and analytics companies, have elevated AWS into first place as the leader in vision, as well as ability to execute. At its recent re:Invent conference, the company unveiled a new generation of enhancements which introduce greater performance and integration to its cloud-based databases services.
AWS ushered in the cloud computing era in 2006 with its online capacity offerings and continues to grow today. The company entered the highly competitive database market in 2007 with the launch of Amazon SimpleDB in 2007, and Amazon RDS two years later.
The introduction of AWS’s all-cloud databases was not only a challenge to the status quo with a landscape of well-entrenched vendors, but a response to customer demand for databases that were easy to set up, operate, and scale without worrying about upfront investment and time-consuming administration tasks. Customers could just focus on their applications and their business.
Amazon’s own pioneering experience from operating its giant e-commerce business has provided a wellspring of experience for what it takes to build massive, modern, internet-scale databases that serve customers around the world. AWS achievement as the leader of leaders in the 2022 Gartner Magic Quadrant for Cloud DBMS, at a time when cloud adoption is fueling massive growth in the database market, is a strong signal that AWS’s obsession with understanding and delivering for customers is continuing to lead the way.
“AWS achievement as the leader of leaders in the 2022 Gartner Magic Quadrant for Cloud DBMS, at a time when cloud adoption is fueling massive growth in the database market, is a strong signal that AWS’s obsession with understanding and delivering for customers is continuing to lead the way.”
While AWS releases innovations throughout the year, its focal point for announcements towards the end of the year is re:Invent, its annual developer conference. At 2022 re:Invent in November, AWS announced significant advancements for its database services, including service integration, scale and performance, and operational excellence.
Over the coming year, AWS intends to increase interoperability across its services, further automating time-consuming efforts involving data transfers between database and analytical environments. The company will launch Amazon Aurora Zero-ETL to Amazon Redshift, designed to deliver interoperability between Amazon Aurora, AWS’s leading operational database, and Amazon Redshift, its leading analytical database. This capability replicates transaction data written to Amazon Aurora within seconds to Amazon Redshift.
Multiple Amazon Aurora databases can replicate data to the same Amazon Redshift database, providing faster insights from unified data to empower analytics that require near-real-time data. There are a number of performance optimization techniques that continuously move data across databases without disruption to the databases on either end of the data pipeline. The data movement occurs in parallel and the integration itself is elastic and serverless, so capacity is adjusted as needed. Customers can continue running analytic queries on Amazon Redshift alongside parallel data ingestion.
Unlike a complex extract, transform, and load (ETL) or extract, load, and transform (ELT) implementation using a generalized tool and custom coding, AWS built this integration to be highly maintainable. For instance, it adapts to Aurora side schema changes. Database or table additions and deletions are handled transparently. If a transient error is encountered the integration automatically re-synchronizes after the recovery from the error.
Scale and Performance
AWS also made key announcements related to performance prior to re:Invent. The company released Amazon Aurora Serverless v2 (ASv2) in early 2022, enabling customers to deploy Aurora on-demand with autoscaling where the database automatically starts up, shuts down, and scales capacity up or down based on an application's needs. ASv2 is particularly useful for spiky, intermittent, or unpredictable workloads. Manually managing database capacity can take up valuable time and can lead to inefficient use of database resources. Customers pay on a per-second basis for the database capacity that is used when the database is active.
ASv2 is the fastest growing feature for AWS’s fastest-growing database, Jeff Carter, Vice President of Databases and Migration at AWS, announced at re:Invent. Liberty Mutual and S&P Global, along with other companies, are using ASv2 to take advantage of simplicity and cost savings, he added.
Another key feature that benefits both performance and availability is Amazon RDS with Multi-AZ deployments. In an Amazon RDS Multi-AZ deployment, Amazon RDS automatically creates a primary database instance and synchronously replicates the data to an instance in a different AZ. When it detects a failure, Amazon RDS automatically fails over to a standby instance without manual intervention.
AWS released Amazon RDS Multi-AZ with two readable standbys in different AZs in March 2022, incorporating an additional layer of protection as well as significant performance benefits. Failovers typically occur in under 35 seconds with zero data loss and no manual intervention. Customers can gain read scalability by distributing traffic across two readable standby instances. Another benefit is that customers can gain up to 2x improved write latency compared to Multi-AZ with one standby. Multi-AZ with two standbys is available for Amazon RDS for PostgreSQL and RDS for MySQL.
At November’s re:Invent, performance optimizations were featured in announcements related to Amazon DocumentDB and Amazon RDS. Like other AWS databases, Amazon DocumentDB addresses read performance through horizontal scaling of read replicas. The key new innovation on top of this is the horizontal scaling of writes. With Amazon DocumentDB Elastic Clusters, Amazon DocumentDB now uses sharding or partitioning, so that writes can be performed on any partition and the write is replicated to all the other partitions in a multi-active configuration. The net result is high throughput for both reads and writes as well as support for storage of petabytes of data.
AWS announced read and write performance improvements to single instances of RDS for MySQL. Amazon RDS Optimized Writes enhances the internal implementation of atomic writes. Previously, under the covers, atomic writes required two writes, one to an internal buffer and the second to storage. This enhancement writes atomically with a single write, which delivers the 2x writes throughput improvement.
Similarly, Amazon RDS Optimized Reads runs queries up to 50% faster. For complex queries like those that require grouping or sorting, RDS for MySQL stores intermediate results in a temporary table. Optimized Reads locates these intermediate results in the instance’s local storage, rather than shared network storage such as an Amazon Elastic Block Store (EBS) volume. The local availability of temporary data accelerates the queries.