article thumbnail

Use Apache Iceberg in a data lake to support incremental data processing

AWS Big Data

How Apache Iceberg addresses what customers want in modern data lakes More and more customers are building data lakes, with structured and unstructured data, to support many users, applications, and analytics tools. The snapshot points to the manifest list.

Data Lake 116
article thumbnail

Architectural patterns for real-time analytics using Amazon Kinesis Data Streams, part 1

AWS Big Data

This is the first post to a blog series that offers common architectural patterns in building real-time data streaming infrastructures using Kinesis Data Streams for a wide range of use cases. In this post, we will review the common architectural patterns of two use cases: Time Series Data Analysis and Event Driven Microservices.

Analytics 111
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Exploring real-time streaming for generative AI Applications

AWS Big Data

Furthermore, data events are filtered, enriched, and transformed to a consumable format using a stream processor. The result is made available to the application by querying the latest snapshot. For building such a data store, an unstructured data store would be best.

article thumbnail

Choosing an open table format for your transactional data lake on AWS

AWS Big Data

Offers different query types , allowing to prioritize data freshness (Snapshot Query) or read performance (Read Optimized Query). Clustering data for better data colocation using z-ordering. Considerations Data skipping using metadata column stats has to be supported in the query engine (currently only in Apache Spark).

Data Lake 113
article thumbnail

Orca Security’s journey to a petabyte-scale data lake with Apache Iceberg and AWS Analytics

AWS Big Data

To overcome these issues, Orca decided to build a data lake. A data lake is a centralized data repository that enables organizations to store and manage large volumes of structured and unstructured data, eliminating data silos and facilitating advanced analytics and ML on the entire data.

article thumbnail

Big Data, Big Benefits: What Leaders Say

Sisense

In his article in Forbes , he discussed how some of the biggest names in global business — Nike, Burger King, and McDonald’s — and progressive newer entrants to huge sectors like insurance, are embracing data and analytics technology as a platform on which to build their competitive advantages. Organizations must adapt or die.