Category: Analytics

As organizations adopt and deploy home-connected smart devices, they face challenges utilizing device telemetry data in narrow and broad contexts. Examples of such home-connected devices are smart meters and home sensors that emit telemetry and measurements as time series data. In a narrow context, operational teams use data to understand if devices are operating within […]

There are many scenarios in which you might need to migrate your Amazon DynamoDB tables from one AWS account to another AWS account, such as when you need to consolidate all your AWS services into centralized accounts. Consolidating DynamoDB tables into a single account can be time-consuming and complex if you have a lot of […]

Amazon Quantum Ledger Database (Amazon QLDB) is a fully managed ledger database that provides a transparent, immutable, and cryptographically verifiable transaction log. You can use Amazon QLDB to track each application data change, and it maintains a complete and verifiable history of changes over time. Because of those key features, banking customers have adopted Amazon QLDB as a database […]

This is a guest post by Sergey Podlazov – Director of Engineering (Shopping Experience) at Zulily, Senthil Kumar, Sr. Solutions Architect, AWS, and Praveen Chamarthi, Sr. Technical Account Manager, AWS Zulily offers a unique ecommerce experience to shoppers by offering amazing deals on products for moms, kids, and babies. We have scaled this model to […]

When using a document data store as your service’s source of truth, you may need to share the changes of this source with other downstream systems. The data events that are happening within this data store can be converted to business events, which can then be sourced into multiple microservices that implement different business functionalities. […]

Amazon DynamoDB is a key-value and document database that delivers single-digit millisecond performance at any scale. It’s a fully managed, multi-region, multi-active, durable database with built-in security, backup and restore, and in-memory caching for internet-scale applications. DynamoDB can handle more than 10 trillion requests per day and can support peaks of more than 20 million […]

Many organizations have accelerated their adoption of stream data processing technologies in an effort to more quickly derive actionable insights from their data. Frequently, it is required that data from streams be computed into metrics or aggregations and stored in near real-time for analysis. These computed values should be generated and stored as quickly as […]

Hundreds of thousands of customers use Amazon DynamoDB for mission-critical workloads. In some situations, you may want to migrate your DynamoDB tables into a different AWS account, for example, in the eventuality of a company being acquired by another company. Another use case is adopting a multi-account strategy, in which you have a dependent account […]

AWS Database Migration Service (DMS) announced support of Amazon Managed Streaming for Apache Kafka (Amazon MSK) and self-managed Apache Kafka clusters as target. With AWS DMS you can replicate ongoing changes from any DMS supported sources such as Amazon Aurora (MySQL and PostgreSQL-compatible), Oracle, and SQL Server to Amazon Managed Streaming for Apache Kafka (Amazon MSK) and self-managed Apache Kafka clusters.
In this post, we use an e-commerce use case and set up the entire pipeline with the order data being persisted in an Aurora MySQL database. We use AWS DMS to load and replicate this data to Amazon MSK. We then use the data to generate a live graph on our dashboard application.

In this post, we show you how to integrate Amazon DocumentDB with Amazon ES so you can run full text search queries over your Amazon DocumentDB data. Specifically, we show you how to use an AWS Lambda function to stream events from your Amazon DocumentDB cluster’s change stream to an Amazon ES domain so you can run full text search queries on the data.