AWS Database Blog

Category: Amazon Aurora

Access Amazon Location Service from Amazon Aurora

Organizations typically store business and customer data in databases like Amazon Relational Database Service (Amazon RDS) and Amazon Redshift, and often want to enrich this data by integrating with external services. One such enrichment is to add spatial attributes such as location coordinates for an address. With the introduction of Amazon Location Service, you now […]

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Monitor errors in Amazon Aurora MySQL and Amazon RDS for MySQL using Amazon CloudWatch and send notifications using Amazon SNS

Monitoring databases is essential for any DBA, from dev-test databases to mission-critical databases. You want to capture system and user-defined events for monitoring and troubleshooting problems related to your database instance. MySQL records these events in error logs. In this post, we show you how to monitor different events, such as deadlocks, access denied errors, […]

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Schedule jobs with pg_cron on your Amazon RDS for PostgreSQL or Amazon Aurora for PostgreSQL databases

Scheduling jobs is an important part of every database environment. On a traditional on-premises database, you can schedule database maintenance jobs on the operating system where the database runs. When you migrate your databases to Amazon Relational Database Service (Amazon RDS) or Amazon Aurora, you lose the ability to log in to the host and […]

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Migrate Azure SQL Database to Amazon Aurora using Azure Data Sync Agent and AWS DMS

Increasingly, customers are looking to break free from their legacy database (e.g., Oracle and Microsoft SQL Server) and move to a cloud-native database such as open-source engines running on AWS. One of the preferred destinations for this data is Amazon Aurora. In this post, we walk through a migration of a Microsoft Azure SQL database […]

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Introducing binlog I/O cache in Amazon Aurora MySQL to improve binlog performance

Binlog replication is a popular feature serving multiple use cases, including offloading transactional work from a source database, replicating changes to a separate dedicated system to run analytics, and streaming data into other systems, but the benefits don’t come for free. Binary logging can limit database performance (higher commit latency and lower throughput) because the […]

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Deploy multi-Region Amazon Aurora applications with a failover blueprint

Certain organizations require multi-Region redundancy for their workloads to achieve disaster recovery and business continuity. Disaster recovery is an important part of resiliency strategy and concerns how a workload responds when a disaster strikes. The most common pattern to have as a disaster recovery solution in AWS is to build a multi-Region application architecture including […]

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Use Python SQLAlchemy ORM to interact with an Amazon Aurora database from a serverless application

As organizations work to modernize their traditional applications to an event-driven, serverless model, a question that comes up frequently is how the object-relational mapping (ORM) layer should be managed. Packaging it with AWS Lambda functions increases its size and adds a cognitive burden on the development team to track. In addition, many organizations have requirements […]

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Options for legacy application modernization with Amazon Aurora and Amazon DynamoDB

Legacy application modernization can be complex. To reduce complexity and risk, you can choose an iterative approach by first replatforming the workload to Amazon Aurora. Then you can use the cloud-native integrations in Aurora to introduce other AWS services around the edges of the workload, often without changes to the application itself. This approach allows […]

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Monitor Amazon RDS for PostgreSQL and Amazon Aurora for PostgreSQL database log errors and set up notifications using Amazon CloudWatch

Database administrators set up monitoring on database log files to get alerted on certain informational and critical events relating to a pattern of errors specific to a database. Monitoring for errors on a business-critical database is essential to avoid unexpected outcomes such as a missed service-level agreement (SLA), which might result in penalties. A good […]

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How to choose the best disaster recovery option for your Amazon Aurora MySQL cluster

There are many different ways to achieve disaster recovery objectives based on business requirements, but finding the best option for a particular situation can get overwhelming. The innovation and commercial-grade features that come with Amazon Aurora MySQL-Compatible Edition expands these options even further. This post outlines options available to customers running Aurora MySQL, and evaluates […]

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