Category: Amazon Redshift

Learn how the Heimdall Database Proxy can be configured to provide customer query routing for Amazon RDS for Postgres, although any SQL database type including Amazon Redshift can be supported. This provides a single Heimdall Proxy endpoint to access data for multiple customers from multiple databases, transparently. Heimdall Data provides functionality needed to support many complex database environments, and solves many of the challenges in scaling database access.

As organizations acquire more and more data, the need to effectively store and query the data has become very important. Canvas Glide from LTI is a tool for administering Amazon Redshift’s day-to-day routine tasks. It also helps organizations manage all financial aspects related to cost allocation, chargeback, monitoring, and planning of Amazon Redshift clusters. Learn how Canvas Glide assists administrators to successfully manage their clusters and guides them on common maintenance tasks.

Esri and AWS are extending their collaboration through an extensive integration of product suites and services. This includes Amazon QuickSight leveraging Esri basemap tiles through Amazon Location Service. Esri also supports ArcGIS Enterprise on Kubernetes running with Amazon EKS, and interoperability with Amazon Redshift. Esri‘s GIS solutions create, manage, analyze, and map various types of geospatial data. Their flagship GIS mapping software, ArcGIS, is a powerful mapping and spatial analytics technology.

Enterprise data warehouses are complex and consist of database objects that need to be modified to reflect the changing needs of business, data analytics, and machine learning teams. In this post, learn about an approach to managing the evolution of enterprise-scale data warehouses based on the experience of Deloitte’s Data and AI global practice teams. The declarative tool developed by Deloitte that can automatically generate DDL statements to align Amazon Redshift’s state to an approved baseline configuration.

The massive scale and efficiencies offered by cloud data lakes are best served by a continuous replication mechanism from on-premises and cloud-based enterprise resource planning (ERP) applications. Learn how SAP ERP, Amazon Redshift, and HVR Change Data Capture (CDC) add up to more than the sum of the individual parts, and dive deep into HVR’s architecture and the unique value proposition for SAP customers building their data lakes with AWS.

Follow along as Agilisium provides an early look at Amazon Redshift’s ra3.4xlarge instance type (RA3). This post details the result of various tests comparing the performance and cost for the RA3 and DS2 instance types. It will help AWS customers make an informed decision on choosing the instance type best suited to their data storage and compute needs. As a result of choosing the appropriate instance, your applications can perform better while also optimizing costs.

As databases are often a key component of internet infrastructure, IT departments may be challenged by poor connection management from the application. The Heimdall Proxy helps developers, database administrators, and architects horizontally scale out and optimize connections through connection pooling for Amazon Amazon RDS and Amazon Redshift without any application changes. As a result, you will reduce your database instance size and support higher user counts.

Amazon Redshift recently announced support for materialized views, which lead to significantly faster query performance on repeatable query workloads. That, in turn, reduces the time to deliver the datasets you need to produce your business insights. Matillion ETL for Amazon Redshift provides comprehensive enterprise-grade features to simplify and speed up building and maintaining these pipelines.

Change Data Capture (CDC) is the technique of systematically tracking incremental change in data at the source, and subsequently applying these changes at the target to maintain synchronization. You can implement CDC in diverse scenarios using a variety of tools and technologies. Here, Cognizant uses a hypothetical retailer with a customer loyalty program to demonstrate how CDC can synchronize incremental changes in customer activity with the main body of data already stored about a customer.

Effective and economical use of data is critical to your success. As data volumes increase exponentially, managing and extracting value from data becomes increasingly difficult. By adopting best practices that Onica has developed over years of using Amazon Redshift, you can improve the performance of your AWS data warehouse implementation. Onica has completed multiple projects ranging from assessing the current state of an Amazon Redshift cluster to helping tune, optimize, and deploy new clusters.