AWS Big Data Blog

Category: Advanced (300)

Automate replication of relational sources into a transactional data lake with Apache Iceberg and AWS Glue

Organizations have chosen to build data lakes on top of Amazon Simple Storage Service (Amazon S3) for many years. A data lake is the most popular choice for organizations to store all their organizational data generated by different teams, across business domains, from all different formats, and even over history. According to a study, the […]

Monitor Apache HBase on Amazon EMR using Amazon Managed Service for Prometheus and Amazon Managed Grafana

Amazon EMR provides a managed Apache Hadoop framework that makes it straightforward, fast, and cost-effective to run Apache HBase. Apache HBase is a massively scalable, distributed big data store in the Apache Hadoop ecosystem. It is an open-source, non-relational, versioned database that runs on top of the Apache Hadoop Distributed File System (HDFS). It’s built […]

How OLX Group migrated to Amazon Redshift RA3 for simpler, faster, and more cost-effective analytics

This is a guest post by Miguel Chin, Data Engineering Manager at OLX Group and David Greenshtein, Specialist Solutions Architect for Analytics, AWS. OLX Group is one of the world’s fastest-growing networks of online marketplaces, operating in over 30 countries around the world. We help people buy and sell cars, find housing, get jobs, buy […]

Synchronize your Salesforce and Snowflake data to speed up your time to insight with Amazon AppFlow

This post was co-written with Amit Shah, Principal Consultant at Atos. Customers across industries seek meaningful insights from the data captured in their Customer Relationship Management (CRM) systems. To achieve this, they combine their CRM data with a wealth of information already available in their data warehouse, enterprise systems, or other software as a service […]

Automate schema evolution at scale with Apache Hudi in AWS Glue

In the data analytics space, organizations often deal with many tables in different databases and file formats to hold data for different business functions. Business needs often drive table structure, such as schema evolution (the addition of new columns, removal of existing columns, update of column names, and so on) for some of these tables […]

Migrate your indexes to Amazon OpenSearch Serverless with Logstash

We recently announced the general availability of Amazon OpenSearch Serverless , a new option for Amazon OpenSearch Service that makes it easy run large-scale search and analytics workloads without having to configure, manage, or scale OpenSearch clusters. With OpenSearch Serverless, you get the same interactive millisecond response times as OpenSearch Service with the simplicity of […]

Serverless logging with Amazon OpenSearch Serverless and Amazon Kinesis Data Firehose

February 9, 2024: Amazon Kinesis Data Firehose has been renamed to Amazon Data Firehose. Read the AWS What’s New post to learn more. In this post, you will learn how you can use Amazon Kinesis Data Firehose to build a log ingestion pipeline to send VPC flow logs to Amazon OpenSearch Serverless. First, you create […]

Handle UPSERT data operations using open-source Delta Lake and AWS Glue

Many customers need an ACID transaction (atomic, consistent, isolated, durable) data lake that can log change data capture (CDC) from operational data sources. There is also demand for merging real-time data into batch data. Delta Lake framework provides these two capabilities. In this post, we discuss how to handle UPSERTs (updates and inserts) of the […]

Super-charged pivot tables in Amazon QuickSight

Amazon QuickSight is a fast and cloud-powered business intelligence (BI) service that makes it easy to create and deliver insights to everyone in your organization without any servers or infrastructure. QuickSight dashboards can also be embedded into applications and portals to deliver insights to external stakeholders. Additionally, with Amazon QuickSight Q, end-users can simply ask […]

Build a multi-Region and highly resilient modern data architecture using AWS Glue and AWS Lake Formation

AWS Lake Formation helps with enterprise data governance and is important for a data mesh architecture. It works with the AWS Glue Data Catalog to enforce data access and governance. Both services provide reliable data storage, but some customers want replicated storage, catalog, and permissions for compliance purposes. This post explains how to create a […]