Category: Best Practices

By combining DynamoDB streams with Lambda, you can build responsive, scalable, and cost-effective systems that automatically react to data changes in real time. In this post, we explore best practices for architecting event-driven systems using DynamoDB and Lambda. DynamoDB provides two options for capturing data changes (CDC): DynamoDB streams and Amazon Kinesis Data Streams (KDS). In this post, we focus exclusively on DynamoDB streams.

This is a guest post written by Jon Haddad an Apache Cassandra committer specializing in performance tuning, fixing broken clusters, and cost optimization. In this post, we discuss the basics of improving the performance of Amazon EBS with Cassandra to take advantage of the operational benefits. We explore some basic tools used by Cassandra operators to gain insight into key performance metrics. You can then apply these metrics to modify key operating system (OS) tuneables and Cassandra configuration. Finally, we review benchmarks on performance gains by implementing best practices for Amazon EBS.

pgvector is the open source PostgreSQL extension for vector similarity search that powers generative artificial intelligence (AI) applications using techniques such as semantic search and retrieval-augmented generation (RAG). Amazon Aurora PostgreSQL-Compatible Edition has supported pgvector 0.5.1 since 2023. Amazon Aurora now supports pgvector version 0.7.0, which adds parallelism to improve the performance of building Hierarchical Navigable Small Worlds […]

In the post Reduce cost and improve performance by migrating to Amazon DocumentDB 5.0, we discussed various ways to reduce costs by migrating your workload to Amazon DocumentDB. In this post, we demonstrate the document compression feature in Amazon DocumentDB to reduce storage usage and I/O cost.

In this post, we cover important concepts of Aurora provisioned and Aurora Serverless v2 databases including cost, performance, features, and how to determine which to use for your workload type.

In this post, we explore the fundamentals of building containerized applications for Amazon DocumentDB using Quarkus with the Panache ORM library. We cover the processes of containerizing your code, building an image, and deploying it using Amazon ECS with AWS Fargate.

Customers often ask for guidance on how to obtain the count of items in a table or within specific partitions (item collections). In this post, we explore several methods to achieve this, each tailored to different use cases, with a focus on balancing accuracy, performance, and cost.

Amazon RDS for SQL Server now supports Amazon EBS io2 Block Express volumes. These volumes are designed to support all your critical database workloads that demand high performance, high throughput, and consistently low latency. io2 Block Express volumes support 99.999% durability, up to 64 TiB storage, up to 4,000 MiB/s throughput, and up to 256,000 Provisioned IOPS for your most demanding database needs, at the same price as EBS io1 volumes. In this post, we share best practices to use the io2 Block Express volumes with RDS for SQL Server DB instances.

Databases form a key part of any enterprise and managing databases during an M&A requires careful planning and implementation to ensure a smooth transition and to maintain data integrity. In this post, we highlight some of the key considerations for successful database management during a merger or acquisition spanning from data assessment to integration strategies.

For those seeking to achieve consistent database transaction performance, Amazon RDS has introduced a new feature: dedicated log volume (DLV). This feature is an additional storage volume specifically for database transaction logs. In this post, we examine common DLV performance benefits, use cases, monitoring capabilities, and the cost of deployment.