Identify, understand and act on previously hidden value from your data.
Use databases that are optimised for scale, performance and cost for specific workloads.
Save 45% on licensing costs by migrating and optimizing on cloud databases. (aws.amazon.com)
Build a better business with data
Purpose-built databases are designed and optimised to perform specific tasks or handle specific types of data. They are an important part of a modern data strategy because they can improve the efficiency, speed, and reliability of data management and analysis.
By using the right purpose-built database for the specific needs of a project or application, organisations can improve the performance and scalability of their data systems, and ultimately make better use of their data.
15+ purpose built databases
15+ purpose-built engines to support diverse data models, including relational, key-value, document, in-memory, graph, time series, wide column, and ledger databases.
Fully managed databases
Free your teams from time-consuming database tasks like server provisioning, patching, and backups through continuous monitoring, self-healing storage, and automated scaling.
Performance at scale
Start small and scale as your applications grow with relational databases or non-relational databases. Match your storage and compute needs easily, often with no downtime.
Availability & security
Provide full data oversight with multiple levels of security, including network isolation and end-to-end encryption and deliver the high availability, reliability, and security you need for business-critical, enterprise workloads.
Feeding data-driven insights across industries

Modern Data Strategy
Building a data strategy is essential for organisations to stay relevant, competitive, and innovative amidst constant change. Because data is vast, dynamic and comes in many different formats, extracting value can be challenging and to harness data’s full potential requires an end to end modern strategy.
Data Maturity Assessment
The Data Maturity Assessment (DMA) is a 5 point assessment of specific areas contributing to a data strategy to highlight your current state, score your data maturity and highlight a clear roadmap for improvement.
Insights & Events around data
AWS Machine Learning: Transforming Media and Entertainment
One AWS pathway of technology, that has the potential to transform the industry of media and entertainment, is machine…
Workload Optimisation and Improved Audit Logging in Amazon Redshift
Today’s insight takes a broader look at two elements shaping Amazon Redshift into the data warehousing behemoth of the…
Build Event-Driven Data Quality Pipelines With AWS Glue DataBrew
As businesses collect more and more data to drive core processes like decision making, reporting and machine learning…
Reduce the Cost and Complexity of Machine Learning Preprocessing
A week ago, Nate Bachmeier, AWS Senior Solutions Architect, and Marvin Fernandes, Solutions Architect, wrote an…
Collecting, Archiving and Retrieving Surveillance Data With AWS
As a company based within the UK, we are no stranger to the presence of CCTV cameras and the importance of them. With a…
New Features in Amazon Managed Grafana
During late August 2021, AWS made Amazon Managed Grafana generally available. At re:Invent, they launched some new…
Amazon SageMaker Canvas announced at AWS re:Invent
The ability to build systems that can predict business outcomes has become very important within the last few years.…
Prevent Fake Account Sign-ups With AI Using Amazon Fraud Detector
Early November, Anjan Biswas, Senior Solutions Architect at AWS, revealed how you can implement a real-time fraud…