Best cloud data warehouses: Top provider comparison

Today’s businesses generate a ton of data… but most organizations don’t use all of that information to generate useful insights that can increase growth and profitability.

That’s a problem, because the inability to collect, manage, and derive insights from data costs time, money, and other resources.

In many cases, companies have the data, but it’s dispersed across different functions, such as marketing, sales, and product, and is used by each department independently. There’s no efficient, user-friendly, and trustworthy way to merge and combine data for use throughout the organization.

For many startups, early-stage companies, and other organizations, a modern data stack with a cloud data warehouse as the centerpiece, is an ideal way to begin solving these problems. 

Cloud data warehouses are powerful, fast, reliable, cost-effective, and relatively easy to deploy. There’s also no shortage of providers to consider and compare, which makes choosing the best cloud data warehouse for your specific needs a tall order.

In the spirit of continuing to demystify data, we’re going to show you how to find the right fit.  Here’s everything you’re about to learn:

• What is a cloud data warehouse?
• Does an on-premise data warehouse ever make sense?
• When does a company need a cloud data warehouse?
• Considerations and criteria for choosing a cloud data warehouse
• Comparing top cloud data warehouse providers
• Snowflake, Redshift, BigQuery, & Synapse aren’t your only data warehouse options

After reading, you’ll be ready to start comparing vendors to find the best cloud data warehouse for your organization.

What is a cloud data warehouse?

A data warehouse stores data from multiple data sources in a single location to make it easier to access, blend, and analyze. Data warehouses are designed and optimized for large-scale storage of data and quick querying of that data.

A cloud data warehouse is simply a data warehouse that “lives” online. Compared to an on-premise data warehouse, these data repositories don’t require you to purchase or maintain any physical hardware. That means they tend to be less expensive, easier to deploy, and easier to maintain and scale.

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Speaking of on-premise data warehouses, they’re worth learning about. Cloud solutions aren’t automatically better and on-premise data storage is still a viable solution for many companies. 

Does an on-premise data warehouse ever make sense?

Sometimes it seems like it’s cloud-based or bust when it comes to technology, but there’s still a case for on-premise data warehouses. 

An on-premise option makes sense when:

• You already have the server infrastructure needed for an on-premise data storage solution.
• Your current staff roster includes employees who are knowledgeable about maintaining that infrastructure.
• You’re concerned about third-party accessibility issues and would prefer not to store data on someone else’s servers.
• Scalability isn’t a huge concern because your company has predictable data volumes and usage patterns.
• You’d rather not sign any contracts or pre-pay for storage and compute time that you might not need.

Assuming a cloud data warehouse still sounds like the most appropriate solution for your organization, let’s talk about how you know when it’s time to build one in the first place.

When does a company need a cloud data warehouse?

There’s a simple rule of thumb that we like to use to answer questions like this one:

If your organization is frequently asking questions about data that sits in more than one place, it’s a good time to build a modern data stack with a cloud data warehouse at the center.

In our experience, you’ll be golden if you follow that guideline. But, if you want to learn more about specific use cases and real-world scenarios that necessitate a data warehouse, here are a few more.

Considerations and criteria for choosing a cloud data warehouse

If you decide that a cloud data warehouse is a good fit for your organization’s needs, here’s the initial list of criteria to assess when comparing vendors:

1. Data types: The types of data your company needs to store (and the types of data the warehouse supports), including unstructured raw data, semi-structured data, and structured data.

2. Scalability: The ability to increase or decrease the level of storage and compute as needed, based on factors like how much data you need to store and how many queries you need to run.

3. Speed, performance, latency, and concurrency: Aka how quickly you can access your data when it’s queried, particularly during high-demand periods when multiple queries are running concurrently.

Real-time analytics may be necessary for companies and teams that use data to guide immediate, reactive actions (like logistics and finance). However, most analyses don’t really need real-time data analytics. Keep this in mind as you assess providers because true real-time analytics costs a lot more. 

4. Startup and ongoing maintenance: There’s a cloud data warehouse for every level of technical ability, so determine the amount of engineering resources you’re willing to allocate to startup and maintenance.

If you have a smaller team with a few data engineers who are in high demand, you probably don’t want them to spend their precious time maintaining your warehouse. On the flip side, a cloud data warehouse that requires more maintenance generally gives you more control, which could be a plus for teams with experienced data warehouse administrators.

5. Integration with existing tools in your data stack: A cloud data warehouse isn’t very useful if it doesn’t integrate with the tools you already use. 

Many cloud data warehouses play nicely with different data sources, data ingestion tools, BI tools, and other layers of the modern data stack. However, you should never assume that an integration exists – always confirm with each provider you’re considering. 

6. Cost and pricing structure: Calculating the cost of a cloud data warehouse can be tricky and prone to volatility. Generally, costs are determined based on consumption and compute time:

• Consumption-based pricing is based on the amount of data queried. This pricing model is easier to calculate but costs can balloon depending on usage. 
• Compute-based pricing is calculated based on CPU, RAM, and disk usage from running queries. Compute needs are generally more predictable but the upfront investment is higher.

⭐️ Pro Tip: If you’re a non-technical business leader who won’t handle implementation or maintenance, spend time familiarizing yourself with the pricing models of different providers. To make the best decision, you’ll want a solid understanding of the different options and how they fit into the organization’s overall needs.

Comparing top cloud data warehouse providers

If you’ve already started researching the best cloud data warehouse providers, you know that there are plenty of options to choose from. 

To help cut through the noise, we’ve put together this quick comparison table of four cloud data warehouses that the AirOps Team often recommends to startups, early-stage companies, and other organizations that consult with us.

Assess this table alongside the criteria we just reviewed to find an option that will work for your organization’s data analytics needs.

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Snowflake, Redshift, BigQuery, & Synapse aren’t your only data warehousing options

These four cloud data warehouse providers are commonly used and tend to suit most use cases that startups and early-stage companies have in regards to collection, storage, and querying of data. 

They’re far from the only players in the game, though. Here are some additional types of data storage you might consider:

Data lakehouses

First, there were data warehouses to store structured, filtered data that had already been processed for a specific use. 

Next, there were data lakes that could store a mix of structured, semi-structured, and unstructured data. 

Then came the next volume in the cloud data storage saga: data lakehouses, which combine features of both. 

Databricks is one data lakehouse provider that’s becoming more popular. If you want the reliability, governance, and performance of a data warehouse combined with the flexibility and machine learning capabilities of data lakes, it’s an option worth considering.

Relational databases

Who’s to say you need a full-fledged cloud data warehouse at all? You can also use an on-premise or cloud-based relational database in lieu of a data warehouse.

Many smaller companies use relational databases as their data warehouse. They’re great for data that’s largely transactional (i.e., read from and written to). Relational databases are cheaper, more agile, and have relatively simple data models. 

IBM’s Db2 database is one specific provider that we often recommend. Postgres is another popular option that’s free and open-source.

Budget-friendly option for AWS

Firebolt deserves an honorable mention for any organization that’s looking for a cost-effective data warehouse solution that integrates with other technologies and services running on AWS cloud infrastructure.

There’s a caveat, though: You’ll need technical engineering and data team resources to get Firebolt up and running.

So, which cloud data warehouse is best for my company?

We touched on this question in a previous blog post about data warehouses, and perhaps disappointingly, the answer is, “It depends on what you need.”

We always recommend that organizations review documentation and request quotes from any cloud data warehouse providers they’re interested in. Each of the four main providers that we’ve profiled also has a free trial version that you can take advantage of. 

Ideally, you’ll be able to work through the cloud data warehouse selection process with a data expert on your team. If you don’t have those resources in-house, you can also find an outsourced consultant to help you choose the tech that will go into your modern data stack.

Even though we can’t tell you which cloud data warehouse solution is best for your company, we can connect you with the resources you need to make important decisions about your company’s data analytics and BI program. Be sure to check back in with the AirOps blog for the latest and greatest. 

We’re also hard at work on something very exciting that will help more people unlock the power of data in their organizations. If you want to be the first to know about our upcoming product launch, click here to subscribe to our email list and receive the latest updates.

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