What is a cloud data warehouse?
What is a cloud data warehouse?
Businesses have always valued the ability to rapidly collect, process and analyze data. Traditionally, they relied on data warehouses to store data from different sources, but the modern data stack has quickly moved to cloud data warehouses.
A cloud data warehouse beats out on-premise storage regarding affordability, flexibility, agility and scalability.
Enterprises and businesses of all sizes are turning to cloud warehouses as they look for an integrated solution, with some even choosing hybrid storage models.
In this article, we’ll explain what a cloud data warehouse is and why it’s a better alternative to a traditional data warehouse. We’ll also summarize the top three cloud service providers.
What is a cloud data warehouse?
A data warehouse is a centralized storage system for structured data. The data stored here is used for reporting, analytical processing and business intelligence.
You can have multiple data warehouses for different departments within your organization or utilize an enterprise data warehouse to store data from all business areas.
Rather than use a traditional on-premise data warehouse, modern businesses can save resources while efficiently handling their data storage needs by using a cloud-based data warehouse.
A third-party vendor provides a cloud data warehouse. Businesses pay a subscription fee to use the vendor’s cloud infrastructure, which has its hardware and software. The vendor’s software will give you access to the online warehouse.
Cloud warehouses are cheaper and easier to install since the vendor has their infrastructure. Moreover, most cloud data warehouse services perform routine maintenance and implement regular updates.
Cloud-based storage systems are also more flexible and scalable. They can be adapted to handle varying analytical requirements without having to make major changes to the infrastructure. Businesses can also upgrade or downgrade their payment plans to get only the necessary components.
There are three leading cloud data storage solutions — BigQuery, Amazon Redshift and Snowflake — and managers must pick a data pipeline solution that works with all of them.
A fully managed data integration platform like Fivetran, for example, uses data connectors to work with most leading cloud storage vendors.
7 key advantages of a cloud data warehouse
Organizations prefer a cloud data warehouse over a traditional one because they provide seven major advantages.
Let’s take a closer look.
1. Data storage
An on-premise data warehouse can handle a limited amount of data depending on available resources and systems. Once the limit is crossed, organizations need to invest in building additional systems, which could take days or weeks. This hinders query performance, data management and analysis
Alternatively, cloud data warehouse vendors offer limitless data storage. If you exceed the current limit, simply upgrade your plan to increase your storage instantly.
A cloud data warehouse can also be modified to handle unstructured data using transformation via schemas. Hybrid storage like a data lakehouse is also an option.
A traditional data warehouse will provide data access to certain systems at specific locations.
Comparatively, a cloud data warehouse gives analysts and business intelligence tools access to data in near real-time from anywhere, at any time.
Easier access to data means analysis is not hindered by time or location constraints. This speeds up data analysis and leads to faster reporting.
Scaling a traditional data warehouse requires significant investment, both in time and money. New equipment must be installed to work with existing systems so your growing company can handle more data.
A cloud data warehouse can rapidly scale up by upgrading your current payment plan with the vendor. Typically, this slightly increases existing subscription fees and costs less than manual on-premise scaling.
A cloud data warehouse requires no physical setup. You sign up with a vendor platform and then use their features and in-built tools to construct a database.
This eliminates spending on purchasing materials and hiring multiple engineers to install and integrate an on-premise data warehouse.
Cloud data warehouse vendors usually charge a monthly or annual subscription fee, which is far more affordable than a manual installation. They also offer a pay-as-you-go model that allows for incremental scaling.
Easier access, diverse data storage options and better computing capabilities lead to effective business insights. A cloud data warehouse can handle parallel processing, significantly improving analytical query processing.
Physical resources and systems limit a traditional data warehouse’s capabilities. For example, many complex queries can increase server load and reduce performance.
These limitations are eliminated while using cloud storage since most vendors use load-balancing mechanisms to ensure optimum performance.
Cloud data warehouse vendors provide software with a dynamic user interface that is easy to operate for engineers, developers and analysts. Every team has access to the data they need instantly.
Moreover, organizations can use cloud data solutions like Fivetran to go beyond data collection and storage. These platforms help you create an entire data pipeline without any code with features like pre-built integrations, custom dashboards and automation.
Integrating cloud systems is the best way to boost productivity without adding complexities.
For traditional data warehouses, the quality of your hardware and software, along with your engineers, determines availability. Outdated or overloaded hardware will lead to downtimes, so engineers are stuck with stale or unusable data.
On the other hand, most cloud data warehouse vendors guarantee an uptime of 99.9 percent. Top providers also offer 24/7 customer support, so any interruptions can quickly be reported and fixed.
Cloud data warehouse architecture
There are two main types of cloud data warehouse architectures.
A cluster-based architecture is typically used to host a data warehouse in hybrid cloud systems. There are multiple server nodes, each with its storage, CPU and RAM. The lead nodes intake queries and assign them to compute nodes to produce results.
Organizations using this architecture must oversee the pipeline to check whether they have enough nodes to handle their queries. This means their engineers spend more time managing capacity, scalability and overall cluster health.
In the serverless model, the cloud service provider fully manages the database clusters within your data warehouse. They will automatically allocate resources to handle query volumes without hindering speed.
Teams need not closely monitor warehouse operations to maintain overall cluster health.
Serverless cloud warehouse providers often offer flexible pricing so that organizations can only pay for what they need.
How to choose a cloud data warehouse vendor
There are three key considerations when choosing a cloud data warehouse provider.
Let’s dive in.
Cloud data warehouse architecture
The first key factor is whether you choose a serverless or cluster-based data warehouse architecture.
While many businesses still use cluster-based models, serverless architecture is becoming more prevalent. This is mainly because a serverless cloud data warehouse provider will manage the backend processes, saving your developers and engineers a ton of time and allowing them to focus on high-impact tasks.
Serverless architecture is easy to scale and beneficial for companies with high data volumes. Most providers offer autoscaling, which can be enabled with a single click. Compared to a cluster architecture, where developers have to install, configure and maintain nodes manually.
The architecture you choose will also depend on your use cases — like reporting, high-performance analytics, big data analytics, machine learning and customer-facing analytics.
Another big consideration for team leaders considering a cloud data warehouse is pricing.
While cluster-based and serverless cloud data warehouses are cheaper than on-premise storage, a cluster warehouse requires some upfront investment to buy and install nodes and supporting systems.
On the contrary, serverless data warehouses have no upfront commitment. You choose a plan that suits you and add on components as needed.
Serverless cloud data warehouses can also reduce operational costs since most vendors take care of monitoring and maintenance. They also have in-built apps and integrations that can help automate processes to save additional time and money.
The migration path from an on-premise data warehouse to cloud-based or hybrid systems will have hiccups. The chosen provider must accommodate these faults and have safety mechanisms to preserve your data.
For example, robust data recovery and restoration features are essential. Your cloud services provider must have mechanisms to prevent data loss and increase fault tolerance.
Integration is also important. On Fivetran, for example, teams can seamlessly work with multiple destinations using connectors. A feature like this can greatly ease adoption issues.
The top 3 cloud data warehouse vendors
There’s no shortage of vendors that offer cloud data warehouse solutions.
Here’s a look at the three most popular cloud data warehouse vendors.
1. Google BigQuery
BigQuery is Google’s serverless cloud data warehouse solution that boasts built-in machine learning, streaming capabilities and multi-cloud analytics. The platform was built for real-time analytics and provides query acceleration via native integrations with Google Cloud’s streaming products and business intelligence applications.
You can seamlessly integrate BigQuery into your data pipeline using Fivetran. We’ve got a detailed setup guide here to help you out. Fivetran can sync with BigQuery as often as every five minutes.
2. Amazon Redshift
Amazon Redshift is one of the first data warehouses to be offered as a cloud service provider and is widely used across industries. They also have a serverless option to speed up analytics and eliminate the need to manage your data warehouse infrastructure.
Redshift provides automated table designs to improve query speeds and the Amazon Redshift Data API lets you quickly access data from multiple sources. Redshift uses a cluster-based architecture that causes storage and performance limitations, but the newer Serverless option eliminates these issues.
You can set up Redshift to work with Fivetran using this guide.
Snowflake is a popular cloud data warehouse provider that enables you to accelerate your analytics via the Data Cloud. It integrates with leading advanced analytics and business intelligence tools and provides an immediately queryable source for your data.
Fivetran is a Snowflake Elite Partner. Industry leaders use these tools together to create automated, zero-maintenance data pipelines with centralized data storage, secure data replication and rapid query resolution.
A cloud data warehouse is a better option for most businesses than an on-premise warehouse. Cloud warehouses eliminate the storage and scaling limitations of traditional systems while also being more affordable and easier to set up.
The cloud data warehouse provider you choose will largely depend on the architecture in place, your use cases, pricing and the ease of migration.
These days most organizations are opting for cloud service providers using serverless infrastructures since they are fully managed, cost-effective and scalable.
Fivetran is the perfect data integration and pipeline solution to work with your cloud service provider. Get a free trial today to see how we can effortlessly power faster insights and analysis for your team.
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