AWS Big Data Blog

Category: Kinesis Data Streams

Streaming Amazon DynamoDB data into a centralized data lake

For organizations moving towards a serverless microservice approach, Amazon DynamoDB has become a preferred backend database due to its fully managed, multi-Region, multi-active durability with built-in security controls, backup and restore, and in-memory caching for internet-scale application. , which you can then use to derive near-real-time business insights. The data lake provides capabilities to business teams to plug in […]

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Use Grok patterns in AWS Glue to process streaming data into Amazon Elasticsearch Service

Recently, we launched AWS Glue custom connectors for Amazon Elasticsearch Service (Amazon ES), which provides the capability to ingest data into Amazon ES with just a few clicks. You can now use Amazon ES as a data store for your extract, transform, and load (ETL) jobs using AWS Glue and AWS Glue Studio. This integration […]

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Build seamless data streaming pipelines with Amazon Kinesis Data Streams and Amazon Kinesis Data Firehose for Amazon DynamoDB tables

The global wearables market grew 35.1% year over year during the third quarter of 2020, with total shipments reaching 125 million units according to new data from the International Data Corporation (IDC) Worldwide Quarterly Wearable Device Tracker. The surge was driven by seasonality, new product launches, and the health concerns during the global pandemic. Given […]

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Build a data lake using Amazon Kinesis Data Streams for Amazon DynamoDB and Apache Hudi

Amazon DynamoDB helps you capture high-velocity data such as clickstream data to form customized user profiles and online order transaction data to develop customer order fulfillment applications, improve customer satisfaction, and get insights into sales revenue to create a promotional offer for the customer. It’s essential to store these data points in a centralized data […]

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The following diagram illustrates the architecture of this intermediate pipeline to generate training data.

Retaining data streams up to one year with Amazon Kinesis Data Streams

Streaming data is used extensively for use cases like sharing data between applications, streaming ETL (extract, transform, and load), real-time analytics, processing data from internet of things (IoT) devices, application monitoring, fraud detection, live leaderboards, and more. Typically, data streams are stored for short durations of time before being loaded into a permanent data store […]

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Validate, evolve, and control schemas in Amazon MSK and Amazon Kinesis Data Streams with AWS Glue Schema Registry

Data streaming technologies like Apache Kafka and Amazon Kinesis Data Streams capture and distribute data generated by thousands or millions of applications, websites, or machines. These technologies serve as a highly available transport layer that decouples the data-producing applications from data processors. However, the sheer number of applications producing, processing, routing, and consuming data can […]

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Building an ad-to-order conversion engine with Amazon Kinesis, AWS Glue, and Amazon QuickSight

Businesses in ecommerce have the challenge of measuring their ad-to-order conversion ratio for ads or promotional campaigns displayed on a webpage. Tracking the number of users that clicked on a particular promotional ad and the number of users who actually added items to their cart or placed an order helps measure the ad’s effectiveness. Utilizing […]

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Building a scalable streaming data processor with Amazon Kinesis Data Streams on AWS Fargate

Data is ubiquitous in businesses today, and the volume and speed of incoming data are constantly increasing. To derive insights from data, it’s essential to deliver it to a data lake or a data store and analyze it. Real-time or near-real-time data delivery can be cost prohibitive, therefore an efficient architecture is key for processing, […]

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Migrating from Vertica to Amazon Redshift

Amazon Redshift powers analytical workloads for Fortune 500 companies, startups, and everything in between. With Amazon Redshift, you can query petabytes of structured and semi-structured data across your data warehouse, operational database, and your data lake using standard SQL. When you use Vertica, you have to install and upgrade Vertica database software and manage the […]

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Unified serverless streaming ETL architecture with Amazon Kinesis Data Analytics

Businesses across the world are seeing a massive influx of data at an enormous pace through multiple channels. With the advent of cloud computing, many companies are realizing the benefits of getting their data into the cloud to gain meaningful insights and save costs on data processing and storage. As businesses embark on their journey […]

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