Category: Kinesis Data Streams

Customers have been using data warehousing solutions to perform their traditional analytics tasks. Recently, data lakes have gained lot of traction to become the foundation for analytical solutions, because they come with benefits such as scalability, fault tolerance, and support for structured, semi-structured, and unstructured datasets. Data lakes are not transactional by default; however, there […]

Real-time anomaly detection describes a use case to detect and flag unexpected behavior in streaming data as it occurs. Online machine learning (ML) algorithms are popular for this use case because they don’t require any explicit rules and are able to adapt to a changing baseline, which is particularly useful for continuous streams of data […]

Data lakes are a popular choice for today’s organizations to store their data around their business activities. As a best practice of a data lake design, data should be immutable once stored. But regulations such as the General Data Protection Regulation (GDPR) have created obligations for data operators who must be able to erase or […]

This is a guest post co-written with Raghu Boppanna from Vanguard.  At Vanguard, the Enterprise Advice line of business improves investor outcomes through digital access to superior, personalized, and affordable financial advice. They made it possible, in part, by driving economies of scale across the globe for investors with a highly resilient and efficient technical […]

Many use cases are moving towards a real-time data strategy due to demand for real-time insights, low-latency response times, and the ability to adapt to the changing needs of end-users. For this type of workload, you can use Amazon Kinesis Data Streams to seamlessly provision, store, write, and read data in a streaming fashion. With […]

Amazon Redshift is a fully managed data warehousing service that is currently helping tens of thousands of customers manage analytics at scale. It continues to lead price-performance benchmarks, and separates compute and storage so each can be scaled independently and you only pay for what you need. It also eliminates data silos by simplifying access […]

The importance of data warehouses and analytics performed on data warehouse platforms has been increasing steadily over the years, with many businesses coming to rely on these systems as mission-critical for both short-term operational decision-making and long-term strategic planning. Traditionally, data warehouses are refreshed in batch cycles, for example, monthly, weekly, or daily, so that […]

This post was co-written with Mike Zorn, Software Architect at LaunchDarkly as the lead author. LaunchDarkly’s feature management platform enables customers to release features and measure their impact. As part of this platform, SDKs gather event data, and the event ingestion platform consumes and analyzes this data to measure impact. As the platform launched and […]

This post is co-written with Dr. Quan Hoang Nguyen, CTO at Fantom Foundation. Here at Fantom Foundation (Fantom), we have developed a high performance, highly scalable, and secure smart contract platform. It’s designed to overcome limitations of the previous generation of blockchain platforms. The Fantom platform is permissionless, decentralized, and open source. The majority of […]

This is a guest post by Kevin Chun, Staff Software Engineer in Core Engineering at NerdWallet. NerdWallet’s mission is to provide clarity for all of life’s financial decisions. This covers a diverse set of topics: from choosing the right credit card, to managing your spending, to finding the best personal loan, to refinancing your mortgage. […]