In the age of big data, where humans generate 2.5 quintillion bytes of data every single day, organizations like yours have the potential to harness more powerful analytics than ever before. But gathering, organizing, and sorting data still proves a challenge. Put simply, there's too much information and not enough context. The most popular commercial data warehouse solutions like Amazon Redshift say they deliver structured, usable data for businesses. But is this true?

AWS Redshift claims it's the fastest cloud data warehouse on the planet, with "up to 3 times better price-performance than any other data warehouse." But these results depend on the size and scale of your business, and other solutions could prove far more effective. In this guide, we compare Amazon Redshift with other data warehouse platforms like Snowflake and Azure Synapse Analytics. 

Table of Contents

  1. Amazon Redshift Data Warehouse Overview
  2. What are the Benefits of AWS Redshift Data Warehouse? 
  3. AWS Redshift Alternatives and Other Data Warehouse Solutions 
  4. Amazon Redshift Cons
  5. How to Choose the Right Data Warehouse for 2021
  6. Integrate Xplenty With AWS Redshift For the Best Data Warehouse Solution

Customer Story
Customer Story
Keith connected multiple data sources with Amazon Redshift to transform, organize and analyze their customer data.
Amazon Redshift Amazon Redshift
David Schuman
Keith Slater
Senior Developer at Creative Anvil
Before we started with Xplenty, we were trying to move data from many different data sources into Redshift. Xplenty has helped us do that quickly and easily. The best feature of the platform is having the ability to manipulate data as needed without the process being overly complex. Also, the support is great - they’re always responsive and willing to help.
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Amazon Redshift Data Warehouse Overview

Amazon Redshift functions differently from traditional data warehouses. Other platforms, like Snowflake, that store data in rows, can cause multiple queries when arranging and sorting data. Redshift is a column-oriented database management system, which means it stores data in columns, making it quicker to analyze data. (Amazon Redshift says it's 2 times faster than competing products like Snowflake.)

AWS Redshift lets you store data in a data lake before the data goes to the data warehouse. (A data lake contains raw, unsorted data; a data warehouse contains structured data.) One Amazon Redshift user says the ability to integrate data with a data lake has allowed them to "integrate new data sources within hours instead of days or weeks." Another user, posting on the software review website G2.com, says the platform is "easy to learn" and "simple to use," and processes data "fast." (AWS Redshift currently has an average user score of 4.2/5 on G2.) 

For more information on Xplenty's native Redshift connector, visit our Integration page.

Recommended Reading: Xplenty's Comprehensive Guide to Amazon Redshift

What are the Benefits of AWS Redshift Data Warehouse?

As mentioned above, AWS Redshift offers users fast speeds. But it also scores points among users for value for money, providing organizations with a fast and powerful data warehouse at a comparatively modest cost. Prices start from $0.25 per hour, cheaper than Snowflake's $2.01 per hour

There are other benefits as well. You can customize AWS Redshift with additional nodes to increase power for large data sets, letting you analyze data without reducing query response times. Amazon Redshift also comes with security protocols to protect sensitive data, such as the following:

  • SSL encryption for data in transit. 
  • Encryption for client-side and server-side data. 
  • Column-level access control.
  • Access management.
  • Sign-in credentials.

This helps you adhere to GDPRHIPAACCPA, and other data governance frameworks. 

Customer Story
Customer Story
Keith connected multiple data sources with Amazon Redshift to transform, organize and analyze their customer data.
MongoDB MongoDB
Amazon Redshift Amazon Redshift
David Schuman
Dave Schuman
CTO and Co-Founder at Raise.me
They really have provided an interface to this world of data transformation that works. It’s intuitive, it’s easy to deal with [...] and when it gets a little too confusing for us, [Xplenty’s customer support team] will work for an entire day sometimes on just trying to help us solve our problem, and they never give up until it’s solved.
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Amazon Redshift Alternatives and Other Data Warehouse Solutions 

As impressive as Amazon Redshift is, it's just one data warehouse solution on the market, competing with the following products (among others):

  • Azure Synapse Analytics (formerly known as Microsoft Azure SQL Data Warehouse)
  • Snowflake
  • SAP Business Warehouse 
  • Google BigQuery

Both individual users and expert analysts have compared the above data warehousing solutions on features, capabilities, pricing, and other factors. User reviews on G2 reveal the following about AWS Redshift alternatives: 

  • Microsoft Azure Azure Synapse Analytics: Azure is not as cost-effective as Redshift but provides better support. (Average user score: 4.4/5.)
  • Snowflake: More flexible and usable than Redshift. (4.6/5.)
  • SAP Business Warehouse: More expensive than Redshift. (3.7/5.)
  • Oracle Autonomous Data Warehouse: More expensive than Redshift. (4.5/5.)
  • Google BigQuery: More intuitive and easier to administer than Redshift. (4.4/5.)

Recommended Reading: AWS Redshift vs. Google BigQuery

Reviews and use-cases can be subjective, however, and you shouldn't rely on them when choosing a data warehouse. For example, G2 reviewers say Azure Synapse Analytics is more expensive than Redshift. But a recent review from business analytics consultancy Think Big Analytics had high acclaim for Azure, praising its security features, easy-to-use API, powerful data insights, and unified experience:

"Azure Synapse Analytics Data Warehouse software enables users to query their data on their terms and a limitless scale."

AWS Redshift Cons

Conversely, AWS Redshift might be too easy to scale, with the ability to improve disk space and power via a few modifications to the AWS Console. At least one Redshift user has written about this online. We think:

  • While quick scalability might prove invaluable for users with particularly large volumes of data, most companies won't benefit from this at all.
  • If Amazon Redshift is too robust, it might cost you more money in the long-term.
  • Redshift does let you scale back processing speeds and power, but you could then experience a spike in volume that the system won't be able to handle.

Furthermore, one user on G2 thinks AWS Redshift needs a better query analyzer; another user thinks the GUI is too complex for first-time users. 

How to Choose the Right Data Warehouse for 2021

As is the case when choosing any commercial application, you must start with a clear understanding of your business requirements. Then ask yourself the following questions:

  1. Do you expect to scale up data processing and data storage?
  2. Do you experience spikes in data volume and require a customized solution?
  3. What's your budget?
  4. Do you need accessible support from your solution provider?
  5. Do you need an intuitive and user-friendly solution?

Develop a framework for data processing requirements, and you'll find a data warehouse solution with cloud services that provide the right amount of power, functionality, and high performance for data analytics. 

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Integrate Xplenty With AWS Redshift For the Best Data Warehouse Solution

There's one last thing to consider when deciding whether Amazon Redshift is the best data warehouse for you: How do you move all your data into Redshift in the first place? Xplenty's Redshift data integration tool lets you transport data into Redshift via the Extract, Transform, and Load (ETL) process. It works like this: 

  • Extract data from various sources (SaaS systems, legacy systems, apps, etc.). 
  • Transform data into a readable, usable format.
  • Load data into AWS Redshift.

All of this eliminates slow database queries on Redshift and executes better data analytics. Once you have extracted, transformed, and loaded data into AWS Redshift, you can connect Redshift to business intelligence tools such as Looker and Tableau for unparalleled data algorithms and real-time insights, helping you make smarter decisions.

Learn more about Xplenty's Redshift integration here.

Want to learn more about how Xplenty is the best ETL data pipeline for Redshift? Contact us to schedule a demo and 14-day risk-free pilot and experience the platform for yourself.