Press release
AWS Announces Three New Database Capabilities
Amazon RDS Custom gives customers a managed service for business applications that require database and operating system customization
Amazon DynamoDB Standard-Infrequent Access (Standard-IA) table class reduces DynamoDB costs by up to 60% for tables that store infrequently accessed data
Amazon DevOps Guru for RDS uses machine learning to better detect, diagnose, and resolve hard-to-find database-related performance issues in minutes not days
As a growing number of applications need to work with petabytes—or even exabytes—of data with low latency and high performance, a one-size-fits-all database no longer meets the needs of customers who require highly available, reliable, and performant ways to leverage and manage data at scale. To meet these demands, more and more customers are looking to choose the right database for their unique needs. AWS offers the broadest and deepest selection of specialized database engines, including DynamoDB for key-value databases, Amazon Neptune for graph databases, Amazon ElastiCache and Amazon MemoryDB for
“Customers have told us they want databases that are optimized for their most important use cases to deliver flexible, scalable, and reliable user experiences without worrying about the resource-intensive burden of managing infrastructure or incurring excess costs,” said
Amazon RDS Custom gives customers a managed database service for business applications that require customization of the underlying database and operating system
Customers who want to run commercial databases like Oracle and Microsoft SQL Server in the cloud choose Amazon RDS because it is easy to set up, operate, and scale. With Amazon RDS, customers no longer need to worry about time-consuming administrative tasks like provisioning capacity, scaling, and backing up their data. However, some business applications require customization to their underlying Oracle and Microsoft SQL Server database environment and operating system (e.g. Microsoft Dynamics AX, Microsoft SharePoint, and Oracle PeopleSoft). Today, customers often run these applications in a self-managed environment (e.g. on Amazon EC2 or on-premises) so they can have full control over the underlying database environment and operating system. While self-managed deployments are highly configurable, customers must spend time on administrative tasks like hardware provisioning, database setup, patching, and backups. What customers running applications that require database and operating system customization want instead is to automate these undifferentiated administrative tasks to make it easier to run these applications on AWS.
Amazon RDS Custom automates the setup, operation, and scaling of the Oracle and Microsoft SQL Server databases that are tightly integrated with common business applications, while allowing customization to the database and underlying operating system these applications require. With Amazon RDS Custom, customers running these types of business applications no longer need to worry about time-consuming administrative tasks like provisioning and scaling hardware, database setup, patching, and backups. Customers can use Amazon RDS Custom to configure their database environment and underlying operating system to modify settings, install custom patches, and integrate third-party software to meet the requirements of their business applications (e.g. custom database minor versions, third-party security and diagnostic software, or specific file system configurations). Amazon RDS Custom automatically monitors the database environment and operating system to detect user-initiated configurations that impact the ability of Amazon RDS Custom to manage the database. If an issue is detected, Amazon RDS Custom will attempt to automatically resolve the issue. For configuration errors that cannot be automatically corrected, Amazon RDS Custom notifies the customer that corrective action is required and provides recommended steps for resolution. Customers can easily move their existing self-managed Oracle and Microsoft SQL Server databases that require specialized customizations to Amazon RDS Custom and no longer worry about having to manage databases themselves. To get started with Amazon RDS Custom, visit aws.amazon.com/rds/custom.
Amazon DynamoDB Standard-Infrequent Access (Standard-IA) table class reduces DynamoDB costs by up to 60% for tables that store infrequently accessed data
Customers choose DynamoDB for high-volume NoSQL workloads because it offers high throughput with consistent millisecond response times at virtually any scale without having to manage servers or clusters. As the patterns of DynamoDB workloads have become more diverse, there is a set of customers who have workloads where storage is the dominant cost for data that needs to be accessed less frequently over time but still requires fast response times when needed. For example, older social media posts, less recent ecommerce orders, and past video game achievements might represent a significant storage expense for customers due to their growing volume and the relatively high cost of storing this data, but they still require high throughput because when this data is requested it needs to be made immediately available. Today, customers optimize costs in these cases by writing code to move older, less frequently accessed data from DynamoDB to lower cost storage alternatives like Amazon S3.
With the new Amazon DynamoDB Standard-IA table class, customers can reduce DynamoDB costs by up to 60% for tables that store infrequently accessed data. The DynamoDB Standard-IA table class offers up to 60% lower storage costs than Standard DynamoDB tables, making it the most cost-effective option for tables where storage is the dominant table cost. In contrast, the DynamoDB Standard table class offers up to 20% lower throughput costs than the Standard-IA table class and remains the most cost-effective option for tables where throughput is the dominant table cost. Customers can switch between DynamoDB Standard and DynamoDB Standard-IA table classes with no impact to table performance and no code changes required to optimize their spend for the type of data they are storing. To get started with the DynamoDB Standard-IA table class, visit aws.amazon.com/dynamodb/standard-ia.
Amazon DevOps Guru for RDS uses machine learning to better detect and diagnose hard-to-find database-related performance issues and provides recommendations designed to resolve them in minutes not days
Amazon DevOps Guru is a machine learning powered service that makes it easier for developers to improve application availability by automatically detecting operational issues and recommending specific actions for remediation. Today, Amazon DevOps Guru alerts customers to operational issues across Amazon RDS engines. However, it can be complicated and time-consuming to determine the exact cause of a database-related issue because developers often need to enlist database administrators to manually run diagnostic tools and queries to determine the factors contributing to the issue. Once the cause of the issue is identified, database experts often need to do additional analysis to fully understand the problem (e.g. analyze database-specific metrics, events, and wait conditions or extract and analyze relevant SQL statements) before providing guidance on how to fix it. As a result, it can take hours or days to uncover and remediate underlying database issues that put application availability or user experience at risk.
Amazon DevOps Guru for RDS is a new machine learning powered capability in Amazon DevOps Guru that is designed to automatically detect and diagnose performance bottlenecks and operational issues in a database and provide detailed remediation recommendations, enabling developers to resolve issues in minutes rather than days. Amazon DevOps Guru for RDS builds on the capabilities of Amazon DevOps Guru for detecting database-related issues to include additional performance-related issues in Amazon RDS (e.g. resource over-utilization and misbehavior of certain SQL queries). Amazon DevOps Guru for RDS is designed to immediately notify developers when issues occur and provide diagnostic information on the root cause, details on the extent of the problem, and intelligent remediation recommendations to help customers quickly resolve database-related performance bottlenecks and operational issues. For example, if an application performance issue related to an unexpected high load on a database is detected, Amazon DevOps Guru for RDS conducts a root cause analysis to find the exact SQL statement causing the issue, sends a notification with the cause and scope of the issue, and recommends corrective actions to resolve the issue quickly. Amazon DevOps Guru for RDS currently works with Amazon Aurora and is planned to support additional Amazon RDS database engines in 2022. To get started with Amazon DevOps Guru for RDS, visit aws.amazon.com/devops-guru/features/devops-guru-for-rds.
NetApp is a cloud-led, data-centric software company that gives companies the freedom to put their data to work in the applications that elevate their business. “NetApp offers cloud services to enable organizations to easily run highly efficient, cost-effective relational database migration and operation programs from on premises to the cloud. However, some organizations running applications that require customization to the database environment and operating system have been unable to move to a fully managed database service in the cloud due to the customizations these applications require,” said
Amazon Fulfillment Technologies designs, develops, and operates fulfillment technology solutions for Amazon fulfillment centers, including automated Amazon Robotics worldwide. “My team manages a large fleet database. Amazon DevOps Guru for RDS helps us identify a wider range of performance anomalies than our threshold-based monitoring without being overly noisy,” said
Singular simplifies marketing data by unifying siloed data, applying attribution, and exposing insights to accelerate growth. “At Singular, we capture, analyze, and refine billions of data points to deliver the most accurate, timely, and actionable cross-platform analytics to our customers. Having immediate access to our data, even if it is infrequently used, is crucial for us to offer our customers the best insights to grow their business fast,” said
NTT DOCOMO, Inc. is a leading mobile phone operator in
Jungle Scout is an all-in-one platform for finding, launching, and selling Amazon products. “Data is the most critical component of our business offering at Jungle Scout. We collect and analyze hundreds of petabytes of data to deliver the most accurate marketplace analytics data in the world to our SMB and Enterprise customers," said
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