Cloud Based Data Warehouse: Top 7 Cloud Data Warehouse Solutions in 2025

Right now, nearly 60% of all corporate data lives in the cloud. That number keeps growing—and for good reason. Businesses are collecting more data than ever before, and most of it isn’t coming from one place. 

That’s why more companies are turning to cloud based data warehouse solutions. These systems are built for speed, scale, and simplicity.

In this guide, we'll explain what a cloud data warehouse is, how it compares to older on-premises systems, and which cloud data warehouse solutions are worth considering in 2025.

It also covers key features, benefits, and everything a business owner should know when choosing the right data warehouse solution. 

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What is a cloud based data warehouse?

A cloud based data warehouse is a type of database that runs on a cloud platform instead of using physical hardware.

It’s managed by a cloud provider like Google Cloud, Microsoft Azure, or Amazon Web Services. The system is designed to store large amounts of data and make it easy to run reports, dashboards, and analytics.

Cloud-based data warehouses are made to work with modern tools. They can pull in data from different sources, handle real-time data, and support both structured and semi-structured data.

That includes data from files, websites, customer systems, and more. You can also build a data pipeline that moves and prepares the data automatically.

Cloud-based data warehouse vs. on-premises data analytics

Trying to decide between a cloud data warehouse solution and an on-premises setup? Let’s break down the key differences so you can choose the right fit for your business.

• Scalability
  
  
  • Cloud data warehouse: Instantly scales storage and compute resources to handle large data volumes.
    
    
  • On-premises data warehouse: Scaling requires hardware upgrades, which are expensive and time-consuming.
    
• Performance
  
  
  • Cloud: Uses columnar data stores and high-performance queries on large data sets.
    
    
  • On-premises: Performance limited by fixed hardware; slower with diverse data sources.
    
• Cost structure
  
  
  • Cloud: Pay-as-you-go model; reduces capital expenditure.
    
    
  • On-premises: High upfront costs for hardware, licenses, and maintenance.
    
• Data access and flexibility
  
  
  • Cloud: Access data in real-time from any location via a cloud platform.
    
    
  • On-premises: Data access is limited to internal networks unless additional VPN or hybrid systems are deployed.
    
• Integration with modern tools
  
  
  • Cloud: Supports data lakes, big data analytics, and data scientists' tooling.
    
    
  • On-premises: Requires custom integration; lacks native support for modern cloud services.
    
• Elasticity
  
  
  • Cloud: Utilizes the elasticity of the cloud to optimize resources.
    
    
  • On-premises: Fixed capacity; inefficient for fluctuating workloads.
    
• Data types supported
  
  
  • Cloud: Handles structured, semi-structured, and unstructured data.
    
    
  • On-premises: Primarily optimized for structured data only.
    
• Maintenance
  
  
  • Cloud: Fully managed by the cloud provider, including updates and patches.
    
    
  • On-premises: Requires in-house IT team for all aspects of system maintenance.
    

Bottom line: What is a cloud data warehouse? A cloud based data warehouse offers more flexibility, lower overhead, and better support for modern data needs than traditional on-premises systems.

Top 7 cloud data warehouse solutions in 2025

Not sure which cloud data warehouse solution to use in 2025? Take a look at the top platforms leading the way and what makes each one stand out.

Google BigQuery

Google BigQuery is a fully managed cloud data warehouse solution designed to support real-time data analytics and big data workloads. It uses a serverless model and automatically manages storage, compute, and data optimization.

Pros:

• Seamless integration with other Google Cloud Platform services
  
  
• Handles petabytes of data with ease
  
  
• Supports real-time data ingestion and updates
  

Cons:

• Complex pricing model
  
  
• Limited cross-cloud capabilities compared to some competitors
  

Snowflake

Snowflake is a cloud based data warehouse that separates compute and storage, allowing for concurrent workloads and dynamic scaling. It runs on multiple cloud infrastructure providers, including AWS, Azure, and Google Cloud.

Pros:

• Supports structured and semi-structured data
  
  
• High performance with data from diverse data sources
  
  
• Native support for data sharing and data governance
  

Cons:

• Costs can rise quickly with heavy usage
  
  
• Customization can be limited compared to self-hosted options
  

Amazon Redshift

Amazon Redshift is part of the AWS ecosystem and is optimized for big data analytics and data warehouse operations. It supports real-time data processing and works well with data pipelines through Amazon Glue and other tools.

Pros:

• Deep integration with AWS services
  
  
• Supports columnar data stores for faster querying
  
  
• Offers managed cloud data warehouse features
  

Cons:

• Scaling can still require some manual tuning
  
  
• Performance may degrade with poorly designed schemas
  

Azure Synapse Analytics (formerly Azure SQL Data Warehouse)

Azure Synapse is Microsoft’s answer to scalable cloud based data warehouses. It merges data lake and data warehouse capabilities, allowing for data across on-premises and cloud environments to be analyzed together.

Pros:

• Ideal for hybrid cloud scenarios
  
  
• Supports real-time analytics on large datasets
  
  
• Built-in connectors for data integration
  

Cons:

• Complex interface for new users
  
  
• Pricing model can be difficult to predict for dynamic workloads
  

Databricks SQL

Built on Apache Spark, Databricks SQL combines big data analytics with data warehousing, supporting structured and semi-structured data in a scalable environment. Ideal for machine learning and data scientists who require fast data access and want to know more about what a cloud data warehouse is.

Pros:

• Supports large-scale data engineering workloads
  
  
• Integrates well with data lakes and cloud storage
  
  
• Provides advanced data pipeline orchestration
  

Cons:

• Not a traditional data warehouse in terms of user experience
  
  
• Steeper learning curve for non-technical users
  

Teradata VantageCloud

Teradata has shifted to the cloud with VantageCloud, offering data warehouse services designed for enterprise-grade performance. This cloud data warehouse solution supports multi-cloud environments and large-scale data integration.

Pros:

• Excellent support for enterprise data governance
  
  
• Scales for high-performance queries on large data volumes
  
  
• Works across different cloud providers
  

Cons:

• Higher cost for smaller teams
  
  
• Still transitioning some legacy features into full cloud-native functionality
  

IBM Db2 Warehouse on Cloud

IBM’s solution provides a fully managed, elastic, and scalable cloud-based data warehouse for transactional and analytical workloads. It focuses on data protection, data governance, and enterprise-level control.

Pros:

• Strong data security and compliance features
  
  
• Good fit for financial and regulated industries
  
  
• Includes data mining tools
  

Cons:

• Smaller community and ecosystem compared to others
  
  
• May not be ideal for startups or SMBs due to the complexity
  

Why your business should invest in cloud data warehouse solutions

Thinking about upgrading how your business handles data? These are the biggest reasons companies are switching to cloud data warehouse solutions right now.

You get faster access to all your data in one place

With a cloud-based data warehouse, your business can combine data from multiple sources into one centralized system.

What is a cloud data warehouse? This solution makes it easier for data analysts, data scientists, and leadership teams to query data, run reports, and make decisions based on real-time numbers. 

Unlike a traditional data warehouse, where storage and computing are locked together, cloud platforms let you manage each separately. This allows you to process data quickly, no matter the amount of data, and only pay for what you use. 

You reduce IT costs while boosting performance

A major reason companies invest in cloud based data warehouse solutions is to cut costs. Managing an on-premises data warehouse means buying servers, setting up cooling, paying for licenses, and hiring people to maintain it.

A cloud-based data warehouse eliminates those problems. The cloud provider handles infrastructure, updates, patches, and performance tuning.

At the same time, the elasticity of the cloud means your warehouse can scale up or down automatically based on demand.

You simplify data integration from multiple sources

Companies today deal with big data that lives in lots of places—CRMs, ERPs, websites, third-party tools, and more.

A modern cloud data warehouse solution brings all this external data together through built-in data integration tools. These systems connect directly with other cloud services, databases, APIs, and file formats.

Instead of manually syncing data, you can automate data ingestion through a data pipeline that keeps everything up to date. 

You gain real-time analytics and reporting

Cloud data warehouses are designed for speed. They support real-time data ingestion and updates, which means dashboards and reports reflect what’s happening at the moment—not hours or days later. 

Traditional systems can't keep up with the volume of data and speed required today. However, with cloud-based data, you can run live reports on everything from website clicks to sales data without delays.

You improve data governance and security

Data privacy laws and compliance requirements continue to grow. What is a cloud data warehouse for businesses? Well, a cloud data warehouse offers built-in data protection tools, access controls, and data governance policies. 

Top cloud data warehouse solutions offer full encryption, detailed audit logs, and automatic backups. Many also meet industry certifications for security and privacy.

Compared to the manual work required with an on-premises data warehouse, these tools are simpler to use and more reliable for protecting your cloud-based data.

You support your team with tools built for modern work

Modern cloud based data warehouses are built to work with tools your team already uses.

From big data analytics platforms to AI and machine learning, these systems connect with today’s leading software and make it easier to analyze data across systems.

Whether you're running advanced data mining projects or just trying to get a quick sales report, cloud-based data warehouse solutions support your entire team—from data engineers to business users.

And since many systems run on public cloud providers like Google Cloud, there’s no need to manage the tech stack in-house.

Key features you should look for in a cloud data warehouse solution

Are you not sure what to prioritize when choosing a cloud based data warehouse solution? These are the must-have features that make all the difference for businesses. 

• Separation of storage and compute: Lets you scale storage and processing independently, reducing costs and improving flexibility.
  
  
• Support for structured and semi-structured data: Handles everything from tables and spreadsheets to JSON and log files, without extra tools.
  
  
• High-performance query engine: Enables fast queries on large data volumes, including real-time data and historical trends.
  
  
• Built-in data integration tools: Connects with apps, platforms, APIs, and external data sources to streamline data ingestion.
  
  
• Strong data governance and access controls: Helps protect enterprise data with built-in roles, permissions, and encryption.
  
  
• Elastic scaling with pay-as-you-go pricing: Grows or shrinks automatically based on workload, with billing tied to actual usage.
  
  
• Integration with modern BI and analytics tools: Works with Power BI, Looker, Tableau, and more, turning your data into actionable insights fast.

So, what is a cloud data warehouse, and how do you choose the best solution? The above features make a cloud data warehouse solution a smart, scalable choice for businesses that need speed, flexibility, and reliable access to data across every part of their operation.

Get started with a cloud based data warehouse today

If your business is struggling with slow reports, scattered systems, or costly hardware upgrades, it’s time to look at a cloud based data warehouse solution.

With faster data access, stronger data governance, and lower costs, you’ll be able to serve your customers better and make smarter decisions every day.

Book a consultation with Trinity Networx and see how we can help you move your data warehouse operations to the cloud—without the hassle.

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Frequently asked questions

What is the difference between a cloud data warehouse and a traditional data warehouse?

What is a cloud data warehouse? A cloud data warehouse solution runs on a cloud platform and is managed by a cloud provider, while a traditional data warehouse runs on physical hardware, often in-house.

The main difference is flexibility—cloud data warehouses typically separate storage and compute, scale easily, and reduce maintenance.

Traditional systems can’t match that, especially when it comes to handling big data, data integration, and real-time data access across the business.

How do cloud based data warehouses provide real-time access to data from multiple sources?

Cloud-based data warehouse solutions are built to support real-time data ingestion and updates. They connect directly with internal systems, third-party tools, and external data sources through a data pipeline.

This gives data analysts and data scientists access to data across disparate data sources without delays, allowing them to query data live and make informed decisions faster.

Why is cloud data warehouse success tied to data integration and governance?

Achieving cloud data warehouse success depends on strong data integration and data governance practices.

Bringing together structured and semi-structured data from different tools requires seamless syncing, while data governance ensures enterprise data stays secure and compliant. 

The right data warehouse solution makes this easier by offering centralized tools to manage data ingestion, access controls, and data quality in real-time.

What types of data can be stored in cloud data warehouse solutions?

A cloud-based data warehouse can store all types of business data—including structured, semi-structured, and unstructured data.

Whether you're dealing with customer info, logs, documents, or media, cloud based data warehouses provide a flexible way to store data in data lakes or columnar data stores. You can then transform this cloud-based data into reports, dashboards, and actionable insights.

How do cloud data warehouses handle large data volumes?

Cloud data warehouses are designed to handle petabytes of data with ease. Thanks to the elasticity of the cloud, the system automatically adjusts to growing data volumes without affecting performance. 

This makes it perfect for big data analytics, especially when working with modern data sets and running high-performance queries on large data from multiple sources.

Can cloud data warehouses support hybrid or multi-cloud environments?

Yes, many cloud data warehouse solutions offer support for on-premises and cloud environments, making it easier to move or sync existing data.

Solutions like Google BigQuery and Snowflake are built to run across different cloud platforms, giving businesses flexibility in how they manage data warehouse operations.

This includes supporting public cloud setups or services in the cloud that align with security or compliance requirements.

What should I look for in a managed cloud data warehouse service?

A reliable managed cloud based data warehouse should include data protection, fast data access, and strong data engineering capabilities. It should offer cloud storage, integration with BI tools, and compatibility with platforms like Google Cloud Platform and Azure SQL Data Warehouse.

Look for a provider that understands your data warehouse is a database—not just a file cabinet—and has the tools to process data, optimize storage, compute, and move data securely across the organization.