AWS Database Blog

Category: Database

Best practices for working with Amazon Aurora Serverless

Amazon Aurora Serverless is an on-demand, auto-scaling configuration for Amazon Aurora. Amazon Aurora Serverless v2, currently in preview, scales instantly from hundreds to hundreds-of-thousands of transactions in a fraction of a second. As it scales, it adjusts capacity in fine-grained increments to provide just the right amount of database resources and supports all manners of database workloads. Amazon Aurora Serverless v1 is a simple, […]

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Explore what’s in store for Amazon RDS at re:Invent 2020

Join us at re:Invent 2020, a free 3-week virtual conference, from November 30 to December 18. This year’s virtual conference is going to be the industry event of the year, offering five keynotes, 18 leadership sessions, and unlimited access to hundreds of sessions, including 10 sessions on Amazon Relational Database Service (Amazon RDS). In this […]

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Building a biological knowledge graph at Pendulum using Amazon Neptune

At Pendulum, we combine state-of-the-art genome sequencing, cell culturing, and manufacturing processes to produce Pendulum Glucose Control, the only medical probiotic clinically shown to lower blood glucose spikes for the dietary management of type 2 diabetes through the gut microbiome. Research and development at Pendulum requires the synthesis of a diverse set of rich data and information streams, and this year we undertook a project to aggregate much of our data into a single database, the Pendulum knowledge graph, which integrates publicly available information on bacterial metabolism with the DNA sequencing data we generate for our strains.

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Deriving real-time insights over petabytes of time series data with Amazon Timestream

Time series data is one of the fastest growing categories across a variety of industry segments, such as application monitoring, DevOps, clickstream analysis, network traffic monitoring, industrial IoT, consumer IoT, manufacturing, and many more. Customers want to track billions of time series monitoring hundreds of millions of devices, industrial equipment, gaming sessions, streaming video sessions, […]

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Collecting, storing, and analyzing your DevOps workloads with open-source Telegraf, Amazon Timestream, and Grafana

Customers asked us to integrate Telegraf with Amazon Timestream, a fast, scalable, serverless time series database service for IoT and operational applications, so we did. Thanks to the Timestream output plugin for Telegraf, you can now ingest metrics from Telegraf agent directly to Timestream.

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Announcing the Amazon DocumentDB (with MongoDB compatibility) workshop

Amazon DocumentDB (with MongoDB compatibility) is a fast, scalable, highly available, and fully managed document database service that supports MongoDB workloads. You can use the same MongoDB 3.6 and 4.0 application code, drivers, and tools to run, manage, and scale workloads on Amazon DocumentDB without worrying about managing the underlying infrastructure. As a document database, […]

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Exploring frequently asked questions with AWS Database Solutions Architects

At Amazon, we listen to our customers and work backward from your needs. Our AWS Database Specialist Solutions Architect team helps you architect your database landscape. In this post, we address 11 frequently asked questions with videos from our Database Specialist Solutions Architects. Let’s begin the learning journey! Migrating to managed database services First, let’s […]

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Setting up Amazon CloudWatch alarms for AWS DMS resources using the AWS CLI

For very large migrations, AWS Database Migration Service (AWS DMS) replication can run for hours or days depending on the data being replicated. It’s advisable to monitor the AWS DMS resources for a smooth migration. Monitoring your resources can help you detect anomalies and trigger notifications based on the threshold metrics configured. You can use […]

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Getting started with Amazon DocumentDB (with MongoDB compatibility); Part 4 – using Amazon SageMaker notebooks

In this post, we demonstrate how to use Amazon SageMaker notebooks to connect to Amazon DocumentDB for a simple, powerful, and flexible development experience. We walk through the steps using the AWS Management Console, but also include an AWS CloudFormation template to add an Amazon SageMaker notebook to your existing Amazon DocumentDB environment.

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Best practices for migrating Oracle database MERGE statements to Amazon Aurora PostgreSQL and Amazon RDS PostgreSQL

To migrate an Oracle database to Amazon Aurora with PostgreSQL compatibility, you usually need to perform both automated and manual tasks. The automated tasks involve schema conversion using AWS Schema Conversion Tool (AWS SCT) and data migration using AWS Database Migration Service (AWS DMS). The manual tasks involve post-AWS SCT migration touch-ups for certain database […]

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