Amazon Redshift vs Microsoft Fabric: Data Platform Comparison
In the age of artificial intelligence, data is becoming the most valuable asset of enterprises. It is the quality and volume of collected information that directly determine the effectiveness of AI models and the conclusions they generate.
Modern analytics platforms, such as Amazon Redshift and Microsoft Fabric, form the foundation for efficient data processing, enabling companies to make strategic decisions based on reliable analyses. We invite you to discover the key differences between Amazon Redshift and Microsoft Fabric to find out which analytical solution best suits your organisation’s specific needs in the era of intelligent technologies.
What are modern data platforms?
A modern data platform is a comprehensive solution that enables management of the entire data lifecycle from acquisition, through storage, processing, to analysis and visualisation.
Unlike traditional systems, modern platforms offer scalability, flexibility, and advanced analytical features, often using the cloud as the operating environment, which eliminates the need to manage physical infrastructure.
What is Amazon Redshift
Amazon Redshift is a fully managed, petabyte-scale cloud data warehouse service based on a massively parallel processing (MPP) architecture.
Designed as a columnar database, it is optimised for complex queries on massive datasets, enabling analysis of both structured and semi-structured data using standard SQL with impressive speed and performance.
The Amazon Redshift architecture is based on clusters consisting of a leader node and compute nodes. The leader node manages communication and task distribution, while the compute nodes, divided into “slices,” process data in parallel.
This architecture ensures high performance for complex queries, scalability to petabytes of data, and automatic recovery from failures.
Strengths
Amazon Redshift stands out with impressive performance for complex queries on massive datasets thanks to its MPP architecture. The platform offers scalability to petabytes of data and flexible deployment options (on-demand, reserved instances). With free Concurrency Scaling credits, the solution provides consistent performance even with thousands of concurrent users. As a mature platform on the market (since 2012), Redshift has proven use cases in various industries, including finance, healthcare, and media and entertainment.
Weaknesses
Amazon Redshift can be costly to maintain and scale, especially with growing datasets. Users may encounter performance bottlenecks as data volume and query complexity increase. The platform also shows certain limitations in parallel data loading and retrieving information from diverse sources. Redshift requires specialised technical knowledge for configuration, optimisation, and maintenance, which can be a barrier for smaller companies without dedicated IT resources.
Integrations
Amazon Redshift offers extensive integration capabilities with ETL tools, BI tools, and AWS partner systems. Particularly interesting is its integration with Oracle solutions such as SQL Developer, ODI Studio, and Data Visualisation. The integration process is simplified thanks to the Amazon Redshift console, which allows quick connection and synchronisation of data with partner applications. Additionally, Redshift integrates with AWS services for seamless data exchange across the cloud ecosystem.
AI and Machine Learning
Amazon Redshift ML enables creating, training, and deploying machine learning models directly using the familiar SQL language. Users can train models on their own data in Redshift to identify trends, predict customer churn, or forecast revenue. Additionally, integration with Amazon Bedrock enables the use of large language models (LLMs) like Claude or Amazon Titan for natural language processing on data in Redshift without the need to export it.
Pricing model
Amazon Redshift offers flexible pricing models tailored to various business needs. You can start with a pay-as-you-go option, with the ability to pause and resume clusters to optimise costs. For steady workloads, Reserved Instances are available with significant discounts. Additionally, each cluster receives up to 1 hour of free Concurrency Scaling credits daily, sufficient for 97% of customers. Users pay only for the resources actually used, enabling spending control.
When to choose Amazon Redshift?
Amazon Redshift is an ideal choice for organisations that need a high-performance cloud data warehouse, especially if they already use the AWS ecosystem. It is suitable for cases requiring a comprehensive analysis of large datasets using SQL, such as financial analysis, fraud detection, or optimisation of clinical research.
Redshift offers flexible deployment and scaling options, allowing resources to be adjusted to changing needs. When choosing Redshift, it is worth considering costs, performance requirements, and needed integrations with other services.
What is Microsoft Fabric
Microsoft Fabric is a comprehensive analytics and data platform that combines a variety of tools in one environment. Based on a SaaS architecture, it integrates components such as Data Factory, Data Engineering, Data Warehouse, and Power BI.
Its central element is OneLake, a unified data repository. Fabric offers built-in AI features, including Microsoft Copilot, enabling task automation and generating intelligent insights.
Microsoft Fabric is based on a SaaS architecture with OneLake at its core, which eliminates data silos. The platform combines all data workloads from data engineering, through warehouses, to real-time analytics.
Benefits include centralised data management, seamless integration with the Microsoft ecosystem, built-in AI capabilities, and a medallion architecture (bronze-silver-gold) supporting data processing from raw to advanced analytics.
See the business guide to Microsoft Fabric
Strengths
Microsoft Fabric stands out with its comprehensive integration of all aspects of data analytics into one platform. A key advantage is OneLake, a unified repository eliminating data silos. Fabric offers a wide range of analytical tools tailored to different roles within an organisation. Native integration with the Microsoft ecosystem (Power BI, Azure, Microsoft 365) ensures a smooth workflow. Built-in AI features, including Microsoft Copilot, automate tasks and deliver intelligent insights. Fabric also enables comprehensive data management with access control and regulatory compliance.
Weaknesses and limitations
Despite its comprehensiveness, Microsoft Fabric has its limitations. The platform is tightly tied to the Microsoft ecosystem, which may hinder integration with other vendors’ solutions. Fabric is a relatively new product, so it has less mature functionalities compared to specialised tools. Multi-cloud flexibility is mainly limited to Azure. The capacity model may be less flexible for organisations with variable computing needs. Additionally, the platform’s complexity can extend the learning curve for new users.
Integrations
Microsoft Fabric offers native integration with the entire Microsoft ecosystem, including Microsoft 365, Microsoft Azure, Microsoft Copilot Studio, and Microsoft Power Platform. It also has numerous connectors to external systems, including Snowflake, Google BigQuery, MongoDB, and AWS S3. Thanks to Data Factory, Fabric can ingest data from diverse structured and unstructured sources. Integration with Power BI provides advanced visualisation capabilities, and connection with Microsoft Azure AI Foundry enables the use of advanced artificial intelligence features.
AI and Machine Learning
Microsoft Fabric offers advanced AI capabilities through integration with Azure Machine Learning in Microsoft Azure AI Foundry and Microsoft 365 Copilot. The platform enables creating, deploying, and managing ML models within a unified environment without switching between tools. AI features are embedded throughout the entire data lifecycle, from engineering to business analysis. Fabric automates routine tasks, creates quick reports, and builds auto-models, making it a good choice for companies seeking integrated AI experiences.
Pricing model
Microsoft Fabric offers two main pricing models: Pay-as-you-go (flexible, no commitments) and Reserved (with savings of up to 40% for annual reservations). Costs depend on two main factors: computing power (Compute) and storage (Storage). A single computing capacity can handle all functions simultaneously and be shared across multiple projects. Fabric also offers three types of licenses for users: Free, Pro, and Premium per-user.
See the Microsoft Fabric licensing and pricing guide
When to choose Microsoft Fabric?
Microsoft Fabric will be the optimal choice for organisations already using the Microsoft ecosystem. It works well for companies looking for a comprehensive solution covering the entire data lifecycle from acquisition to visualisation. It is ideal for enterprises needing integration of different teams (data engineers, analysts, data scientists) on one platform.
Fabric is also suitable for organisations wanting to use advanced AI features without building complex infrastructure, taking advantage of built-in tools supported by Microsoft Copilot.
What is the difference between Amazon Redshift and Microsoft Fabric
Amazon Redshift and Microsoft Fabric represent different approaches to business data analytics.
Redshift focuses primarily on delivering a high-performance cloud data warehouse with a strong emphasis on parallel processing and efficient analysis of large datasets through SQL queries.
Microsoft Fabric, on the other hand, is a comprehensive end-to-end analytics platform that unifies various tools and services (from data engineering to visualisation) into one cohesive SaaS environment.
While Redshift operates in the AWS ecosystem, offering flexible deployment options (on-demand, reserved instances) and integration with Amazon services, Fabric is deeply integrated with the Microsoft ecosystem, including Microsoft 365 and Azure services.
Redshift builds its advantage on maturity and proven performance for large analytical workloads, while Fabric attracts with unifying the user experience, eliminating the need to integrate different tools, and simplifying data management.
The choice between them depends on existing infrastructure, specific analytical needs, and an organisation’s integration preferences.
Which system to choose for a company?
Small company
For a small company, the key factor is ease of implementation and minimising administrative costs.
For a small company, Microsoft Fabric will often be a better choice due to its lower entry threshold, SaaS model eliminating the need to manage infrastructure, and a user-friendly interface that does not require specialised technical knowledge. If the company already uses Microsoft 365 or Power BI, integration will be even easier. Redshift may be a better choice only for small companies deeply integrated with AWS, possessing technical database expertise, or having specific performance and scalability requirements.
Medium company
A medium-sized company should base its choice on existing IT infrastructure and specific analytical needs.
For a medium-sized company, the choice mainly depends on the existing technology ecosystem and available skills. If the organisation already uses Microsoft 365 and Power BI, and the priority is an intuitive analytical environment for different user roles, Microsoft Fabric will be the better choice. Conversely, if the company uses AWS services, has a team experienced in SQL, and needs a high-performance data warehouse with flexible scaling, Amazon Redshift may better meet its needs.
Large company
Large enterprises should make their choice based on IT strategy, existing investments, and a long-term data management vision.
Large companies should often consider a hybrid approach, using both Amazon Redshift and Microsoft Fabric in different areas of the organisation. Redshift is suitable for cases requiring high-performance processing of massive datasets, advanced analytics, and integration with AWS services. Fabric will be a better choice for teams focused on Microsoft 365, needing a unified analytical environment with deep integration with Power BI and Azure. The key is to match the solution to specific use cases and existing IT architecture.
Summary
The choice between Amazon Redshift and Microsoft Fabric should be based on specific business needs, existing technology ecosystem, and available expertise.
Amazon Redshift stands out as a mature, high-performance cloud data warehouse, ideal for organisations needing advanced analysis of large datasets using SQL, particularly in the AWS ecosystem.
Implementing Microsoft Fabric will be a better choice for organisations integrated with the Microsoft ecosystem, valuing ease of deployment, a unified environment, and ease of use without the need to manage infrastructure.
For small and medium-sized companies without extensive IT teams, Microsoft Fabric will often be easier to implement. At the same time, large organisations may consider a hybrid approach, leveraging the strengths of both platforms in different areas of their operations.