AWS Big Data Blog

Category: Amazon Kinesis

Query your data streams interactively using Kinesis Data Analytics Studio and Python

Amazon Kinesis Data Analytics Studio makes it easy for customers to analyze streaming data in real time, as well as build stream processing applications powered by Apache Flink using standard SQL, Python, and Scala. Just a few clicks in the AWS Management console lets customers launch a serverless notebook to query data streams and get […]

Introducing Protocol buffers (protobuf) schema support in AWS Glue Schema Registry

AWS Glue Schema Registry now supports Protocol buffers (protobuf) schemas in addition to JSON and Avro schemas. This allows application teams to use protobuf schemas to govern the evolution of streaming data and centrally control data quality from data streams to data lake. AWS Glue Schema Registry provides an open-source library that includes Apache-licensed serializers […]

Use Amazon CodeGuru Profiler to monitor and optimize performance in Amazon Kinesis Data Analytics applications for Apache Flink

Amazon Kinesis Data Analytics makes it easy to transform and analyze streaming data and gain actionable insights in real time with Apache Flink. Apache Flink is an open-source framework and engine for processing data streams in real time. Kinesis Data Analytics reduces the complexity of building and managing Apache Flink applications using open-source libraries and […]

Make data available for analysis in seconds with Upsolver low-code data pipelines, Amazon Redshift Streaming Ingestion, and Amazon Redshift Serverless

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 […]

Architecture Diagram

Audit AWS service events with Amazon EventBridge and Amazon Kinesis Data Firehose

Amazon EventBridge is a serverless event bus that makes it easy to build event-driven applications at scale using events generated from your applications, integrated software as a service (SaaS) applications, and AWS services. Many AWS services generate EventBridge events. When an AWS service in your account emits an event, it goes to your account’s default […]

How Cynamics built a high-scale, near-real-time, streaming AI inference system using AWS

This post is co-authored by Dr. Yehezkel Aviv, Co-Founder and CTO of Cynamics and Sapir Kraus, Head of Engineering at Cynamics. Cynamics provides a new paradigm of cybersecurity — predicting attacks long before they hit by collecting small network samples (less than 1%), inferring from them how the full network (100%) behaves, and predicting threats […]

Evolve JSON Schemas in Amazon MSK and Amazon Kinesis Data Streams with the AWS Glue Schema Registry

Data is being produced, streamed, and consumed at an immense rate, and that rate is projected to grow exponentially in the future. In particular, JSON is the most widely used data format across streaming technologies and workloads. As applications, websites, and machines increasingly adopt data streaming technologies such as Apache Kafka and Amazon Kinesis Data […]

Gain insights into your Amazon Kinesis Data Firehose delivery stream using Amazon CloudWatch

The volume of data being generated globally is growing at an ever-increasing pace. Data is generated to support an increasing number of use cases, such as IoT, advertisement, gaming, security monitoring, machine learning (ML), and more. The growth of these use cases drives both volume and velocity of streaming data and requires companies to capture, […]

Backtest trading strategies with Amazon Kinesis Data Streams long-term retention and Amazon SageMaker

Real-time insight is critical when it comes to building trading strategies. Any delay in data insight can cost lot of money to the traders. Often, you need to look at historical market trends to predict future trading pattern and make the right bid. More the historical data you analyze, better trading prediction you get. Back […]

Stream Apache HBase edits for real-time analytics

Apache HBase is a non-relational database. To use the data, applications need to query the database to pull the data and changes from tables. In this post, we introduce a mechanism to stream Apache HBase edits into streaming services such as Apache Kafka or Amazon Kinesis Data Streams. In this approach, changes to data are […]