Cloud vs. On-Premises Data Warehouse: Your Comprehensive Guide for 2025

A data warehouse is very much a necessity for modern enterprises, as reflected by the $30 billion market size in 2025, which is expected to increase to $85.7 billion by 2032. The debate has moved from “Should we have a data warehouse?” to “Should we deploy it on-premises or in the cloud?” and that’s precisely the debate we’re looking to settle in this blog.

In the cloud versus on-premises data warehouse debate, both remain popular options for enterprises, each with its unique strengths and ideal use cases. But is one definitively better than the other, or is it all about the organization’s needs? This blog compares cloud data warehouse and on-premise solutions, what their differences are, and when to choose which for your data warehousing.

Cloud vs On-Premises Data Warehouse: What The Debate Is

Data warehouses are built to consolidate data from a variety of sources such as in-house databases and applications, SaaS platforms, and public databases. They serve as a unified repository or a single source of truth for an organization’s analytics and business intelligence (BI) tools.

Data warehouses can be of different types depending on their architecture, model, schema, use cases, and finally, deployment. Organizations have three options when choosing where to deploy their data warehouse: on-premises, cloud, or hybrid.

The traditional data warehouse used to be deployed on-premises, but with the rise of cloud computing, organizations started building data warehouses on the cloud, and many enterprises have also adopted a hybrid cloud data warehouse approach.

The fundamental difference

With an on-premises data warehouse, the organization is also responsible for purchasing, deploying, and maintaining all the necessary hardware and software. However, a cloud data warehouse functions as SaaS, now also known as a data warehouse as a service (DWaaS). This means that it has no physical hardware, and the organization only pays for the storage and cloud computing resources it utilizes.

What’s not different

Regardless of their deployment, data warehouses share certain characteristics. For instance, they use column-oriented databases, which means that data is stored and accessed in columns instead of rows. Plus, data warehouses store both current and historical data and serve as the storage and processing platform for analytics, reporting, dashboards, and business intelligence solutions.

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On-Prem vs. Cloud Data Warehouse: Key Differences

Cloud and on-premises data warehouses differ in several key characteristics, such as infrastructure, scalability, and performance. Here’s a brief overview of the differences before we move on to a more in-depth comparison.

Architecture: Cloud vs. On-Premises

The architectural differences between cloud and on-premises data warehouses contribute significantly to the scalability, cost, and performance of each type.

On-Premises Architecture

Traditional on-premises data warehouses use the three-tier architecture, which includes the bottom, middle, and top tiers or layers.

• Bottom Tier: This is the storage layer, also known as the staging layer, which serves as the foundation for the warehouse. It typically features a database server, data marts, storage devices, and a meta-repository.
• Middle Tier: This is the compute or online analytical processing (OLAP) layer, which is responsible for processing queries.
• Top Tier: This is the services layer, which serves as the user front-end or interface and tools for reporting, analytics, and BI.

Cloud Architecture

Cloud data warehouses don’t follow the conventional architecture, but the catch is that each system features a unique architecture depending on the functionalities and features. Elements such as nodes (computing resources), clusters (groups of nodes), and partitions (slices of nodes) are the same in most cloud data warehouses.

Performance: Cloud vs. On-Premises

On-Premises Performance

Data warehouses built on-premises do offer the ability to tailor hardware specifications for performance requirements and deliver low network latency as all processing happens internally. However, their reliance on the physical location of data and compute resources can limit their performance.

Cloud Performance

Cloud data warehouses utilize distributed computing resources, which allows for parallel processing of data across cloud clusters. The distributed architecture also ensures consistent performance due to the increase in user concurrency.

Despite the consistency in performance, the reliance on network connectivity between the organization and cloud data centers can cause network latency issues.

Cloud vs. On-Premises Data Warehouse: Which Option to Choose?

Choosing between cloud vs. on-prem data warehouse depends on several factors, including your organization’s infrastructure, budget, scalability needs, and compliance requirements. Each option has its own strengths, and the right choice is often dictated by specific use cases.

Choose a Cloud Data Warehouse If…

1. Scalability is a priority: If your organization’s data storage and processing needs fluctuate or are expected to grow rapidly, a cloud data warehouse is ideal. The ability to scale resources up or down on demand ensures you’re not over-provisioning or under-utilizing resources.
2. There are budget constraints: The cloud’s pay-as-you-go pricing model provides a cost-effective solution for organizations looking to avoid the upfront capital expenses associated with purchasing and maintaining physical hardware. It’s especially advantageous for startups or businesses with limited IT budgets.
3. You want ease of maintenance: Cloud service providers handle infrastructure maintenance, updates, and security, freeing up your IT team to focus on higher-value tasks. If your organization lacks a dedicated IT department, this can be a significant benefit.
4. There are geographic distribution and remote teams: For organizations with globally distributed teams or multiple offices, a cloud data warehouse ensures seamless access to data from anywhere with an internet connection. This supports collaboration and consistent data availability.
5. You want advanced features and analytics: Many cloud platforms offer built-in tools for AI, machine learning, and advanced analytics. If leveraging cutting-edge technology is a priority, the cloud provides more accessible options.

Choose an On-Premises Data Warehouse If…

1. You want compliance and data sovereignty: Industries like finance, healthcare, and government often have stringent data security and compliance requirements. An on-premises data warehouse allows you to maintain complete control over your data, ensuring adherence to regulations such as GDPR, HIPAA, or local data sovereignty laws.
2. You have consistent performance needs: If your organization requires low-latency, high-performance analytics and has the infrastructure to support it, on-premises solutions can provide a level of reliability that’s independent of internet connectivity.
3. You need customized solutions: On-premises deployments allow for tailored hardware configurations and specialized optimizations. This level of customization can be critical for businesses with unique or highly specific data processing needs.
4. You’re concerned about data sensitivity: On-premises data warehousing is a good option for organizations handling highly sensitive or proprietary data.

Hybrid Approach: The Best of Both Worlds

A hybrid data warehouse can be an attractive option for enterprises that want to balance the flexibility of the cloud with the control of on-premises solutions. Hybrid warehouses allow businesses to store sensitive or mission-critical data on-premises while leveraging the cloud for scalability, computing power, and advanced analytics.

Data Warehouse Automation with Astera

To wrap up our discussion so far, the choice between a cloud and an on-premises data warehouse is not about which is unequivocally better but rather which aligns best with your organization’s goals, resources, and operational requirements. You can make an informed decision that supports your organization’s data strategy and growth objectives by evaluating your priorities, such as scalability, cost, compliance, and performance.

Whether it’s on-premises or in the cloud, Astera Data Warehouse Builder can help you effortlessly build, deploy, and maintain your data warehouse using next-gen automation.

Astera’s AI-powered automation, end-to-end support, effortless data modeling, and comprehensive data consolidation give you a robust, enterprise-grade solution to complete the entire warehousing process in days instead of months.

Astera’s support for MySQL, Amazon Aurora MySQL, MariaDB, Azure Synapse, and Google BigQuery, lets you build an on-prem or cloud data warehouse hassle-free.

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