Data dictates our work, passions, communications, and information every day. After all, it's data that makes the Information Age tick.
For businesses, this is far from news. Companies have been investing in data collection resources for the better part of the last twenty years.
Today, the challenge isn't collecting data — it’s knowing what to do with it.
In this post, we will cover the ins and outs of data warehouses, the different data warehouses available to your business, and how to choose one that best suits your needs.
What is a data warehouse?
In short, a data warehouse is a more structured and sophisticated database. It stores your data for you, yes, but it also provides context, history, analysis, organization, and possibly even AI parsing.
These extra features make data warehouses an effective way to store vast quantities of data. And by vast, we're talking about data pools that go beyond terabytes. Businesses collect petabytes of data from the apps, communications, and services their teams and customers are using.
For many businesses, this data is currently going to waste. The immense value it can provide is overshadowed by its tremendous size, rendering it unusable. Data warehouses aim to solve this challenge.
When should you choose a data warehouse over a database?
There's not necessarily anything wrong with databases. But for most businesses, a database is too simple to be helpful, especially when a company is pulling data from various sources. It’s similar to how a plain text editor can be used as an integrated development environment (IDE). Still, it’ll never have all the features and capabilities that a purpose-built IDE does.
Data warehouses are built for the modern era. They're capable of taking in data from various sources, including internal databases, third-party apps and services, customer support systems, diagnostics, and so on. This data is not only stored and secured (as it would be in a database), but it's also structured, organized, and analyzed in helpful ways.
In short, a database is valuable when you just need a place to hold a vast quantity of data.
When you want to store vast amounts of data from various sources and work with that data, not just store it, then a data warehouse is the way to go.
Why are cloud data warehouses the best option?
We’ve seen how data warehouses can be more valuable for companies than databases, but how do you know which type to choose? There are two main types of data warehouses: traditional and cloud.
Traditional data warehouses
Companies usually build traditional data warehouses by investing in physical computing hardware (think rooms filled with blinking lights and server racks) and IT personnel. These types of data warehouses have been the standard for a reason: they keep your data on-site, and they feel more secure.
But, there are downsides to this traditional data warehouse structure. Server rooms take up space. And as your company grows, investing in new servers and keeping existing equipment up-to-date can get expensive. But there is another option.
Cloud data warehouses
Just like so many things, data warehouses have started moving to the cloud. Big companies like Google and Amazon offer data storage solutions to customers entirely over the internet. These data warehouses have a handful of benefits, including their ability to keep your data updated in real-time.
Choosing a real-time, cloud-based data warehouse allows you to get started managing your company’s data almost instantly. Just a few clicks and you’re ready to go.
Plus, cloud data warehouses grow with you, letting you quickly scale your business and your data storage and management all at once.
5 best data warehouses
Let’s look at a few of the most popular cloud data warehouses.
Snowflake is one of the most popular and easy-to-use data warehouses out there – generally known as being one of the most modern data warehouses. The flexibility is one of its main selling points. Snowflake is cloud-agnostic, meaning it can be deployed anywhere including AWS, Azure and Google Cloud.
And for many businesses, that's a good thing! You can start using Snowflake almost immediately after pulling your data to it with e.g. Weld. It supports nearly unlimited amounts of data storage, data sources, and concurrent users.
Snowflake is generally one of our most-recommended data warehouse, with BigQuery as the only good alternative. The separation of storage and compute make it simple to manage capacity and ensure fast response times for all warehouse workloads.
2. Google BigQuery
Google BigQuery is Google's offering to the data warehouse industry and resembles most of Google's other software products: It's entirely cloud-based, free (up to 10GB), and super easy to use.
One of the key selling points for BigQuery, aside from its integration with the rest of Google's services, is its analytic capabilities. You can’t overstate Google's ability to work with large amounts of data, and BigQuery is no exception. It offers predictions, insights, and intelligence features, making it a scalable and viable long-term solution. BigQuery is another one of our most-recommended data warehouses.
3. Amazon Redshift
Amazon Redshift is one of the first cloud data warehouses to launch back in 2012 and has been key to drive this trend of data warehousing. That said, they have been slightly behind on development and only recently made efforts to seperate compute and storage – something that Snowflake and BigQuery already had.
Just like Google, Amazon is not one to be left behind in any digital sector. For enterprises, there are few better solutions out there. Amazon Redshift can support exabytes of data (one billion gigabytes), allowing nearly unlimited data storage.
Redshift is an AWS product, a cloud platform that's popular among enterprises. Redshift is a more technical platform, though, so make sure you have a team on hand who can integrate with and manage your Redshift data warehouse.
4. Azure Synapse Analytics
Previously known as Azure SQL Data Warehouse, Azure Synapse Analytics is Microsoft’s version of the data warehouse. This cloud data warehouse is well suited for organizations looking for an easy on-ramp into cloud data warehouse solutions, thanks to its intuitive integration with Microsoft SQL server.
Some its key differentiators include Dynamic Data Masking (DDM), which adds a layer of security by masking sensitive data to non-privileged users. In terms of product features, on top of the enterprise data warehousing, Azure Synapse Analytics offers a unified analytics platform, choice of querying language and end-to-end data monitoring.
One thing to note is that Azure Synapse Analytics is a great data warehousing choice if you’re already using the Microsoft suite of business tools. However, it doesn’t integrate as well with external tools as other data warehousing solutions do.
5. IBM Db2 Warehouse
IBM’s answer to the modern, cloud data warehouse is the Db2 warehouse on cloud. It’s known for its reliability, good transaction control and high availability. It also benefits from IBM’s Netezza technology, meaning that users are equipped with advanced data lookup capabilities. It’s also a good solution for businesses looking to integrate with other IBM tools, as well as Oracle products.
However, we don’t recommend Db2 for small companies that are just getting started with cloud data warehousing, due to its high price point and limited usability features.
Take advantage of the latest data warehouses with Weld
Choosing from the data warehouses available to you is just the first step in building a modern data stack. Businesses can take things to the next level by integrating their data warehouse of choice with Weld. Whether you’re looking for ELT or Reverse-ELT solutions, our products can help you maximize your data’s potential.