AWS Big Data Blog

You can use Apache Kafka to run your streaming workloads. Kafka provides resiliency to failures and protects your data out of the box by replicating data across the brokers of the cluster. This makes sure that the data in the cluster is durable. You can achieve your durability SLAs by changing the replication factor of […]

Amazon Redshift is a fast, fully managed cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. Amazon Redshift uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS designed hardware and machine […]

Apache Kafka is well known for its performance and tunability to optimize for various use cases. But sometimes it can be challenging to find the right infrastructure configuration that meets your specific performance requirements while minimizing the infrastructure cost. This post explains how the underlying infrastructure affects Apache Kafka performance. We discuss strategies on how […]

During the past year, we’ve seen customers running self-managed Elasticsearch clusters on AWS who were running out of compute and storage capacity because of the non-elasticity of their clusters. They adopted Amazon OpenSearch Service. to benefit from better flexibility for their logs and enhanced retention periods. In this post, we discuss how to build a […]

In today’s complex business landscape, organizations are challenged to consume from variety of sources and keep up with data that pours in all through the day. There is a demand to design applications that enables data to be portable across cloud platforms and give them the ability to derive insights from one or more data […]

Amazon Redshift is the most widely used cloud data warehouse. Amazon Redshift makes it easy and cost-effective to perform analytics on vast amounts of data. Amazon Redshift launched Streaming Ingestion for Amazon Kinesis Data Streams, which enables you to load data into Amazon Redshift with low latency and without having to stage the data in […]

Amazon Lookout for Metrics detects outliers in your time series data, determines their root causes, and enables you to quickly take action. Built from the same technology used by Amazon.com, Lookout for Metrics reflects 20 years of expertise in outlier detection and machine learning (ML). Read our GitHub repo to learn more about how to […]

Grafana is a rich interactive open-source tool by Grafana Labs for visualizing data across one or many data sources. It’s used in a variety of modern monitoring stacks, allowing you to have a common technical base and apply common monitoring practices across different systems. Amazon Managed Grafana is a fully managed, scalable, and secure Grafana-as-a-service […]

Organizations typically accumulate massive volumes of data and continue to generate ever-exceeding data volumes, ranging from terabytes to petabytes and at times to exabytes of data. Such data is usually generated in disparate systems and requires an aggregation into a single location for analysis and insight generation. A data lake architecture allows you to aggregate […]

Amazon Redshift is a fast, fully managed, widely popular cloud data warehouse that powers the modern data architecture that empowers you with fast and deep insights and machine learning (ML) predictions using SQL across your data warehouse, data lake, and operational databases. A key differentiating factor of Amazon Redshift is its native integration with other […]