Snowflake vs AWS Redshift: Which Data Platform Should You Choose?

Sector: Technology

Author: Nisarg Mehta

Date Published: 06/27/2025

Snowflake vs AWS Redshift - Blog - image

Contents

Overview of Snowflake
- Key Features of Snowflake
What’s AWS Redshift?
- Key Features of AWS Redshift
Snowflake vs AWS Redshift: Key Feature Comparison
Performance and Scalability
Security and Compliance
Snowflake vs AWS Redshift: Pricing
Conclusion: Which One Should You Choose?
FAQs

When you hear about cloud data platforms, Snowflake and AWS Redshift are probably the first names that pop up. With data growing faster than we can keep up with, businesses really need solutions they can trust to handle all that info, without everything falling apart.

In this post, we’re going to break down both Snowflake and AWS Redshift. We’ll explore what each platform excels at, where they differ, and which one might be the better choice for your needs. By the end, you’ll have a clearer idea of which platform will work best for you.

Overview of Snowflake

Snowflake isn’t your grandma’s data platform, that’s for sure. It’s not just about stashing data away; it’s genuinely engineered to grow right alongside your business. A game-changer from those older systems is how Snowflake intelligently separates compute from storage. What does that mean for you? It means they can scale independently, giving you incredible flexibility – a real lifesaver for businesses wrestling with diverse workloads or truly enormous data volumes.

Key Features of Snowflake

Works Across Clouds: It doesn’t matter if you’re team AWS, Azure, or Google Cloud, Snowflake’s got your back. It makes sharing and moving data a walk in the park across different clouds.
Zero-Copy Cloning: Want to test something? No need to copy data and rack up storage fees. Snowflake’s zero-copy cloning means you can make a test version without doubling up on space.
AI and Machine Learning: Snowflake isn’t just for storing data, it’s ready for AI and machine learning too. With its Snowpark feature, you can run Python and other workloads right in the platform, making it compatible with top AI tools.
Simple Data Governance: Managing data doesn’t have to be a nightmare. Snowflake’s Horizon Catalog keeps everything organized, letting you control who has access and track metadata easily.
Pay for What You Use: No more “surprise” costs. With Snowflake, you only pay for what you actually use. It’s pretty transparent, and you can easily monitor your usage.

What’s AWS Redshift?

So, if you’ve been looking at cloud data options, chances are you’ve heard of AWS Redshift. It’s Amazon’s cloud data warehouse service. The cool part? It’s built to handle huge amounts of data processing, think petabytes, without making you manage all the infrastructure. You get all the power of AWS without having to deal with the complexities.It’s made for people who need to analyze data fast, and it works pretty seamlessly with other AWS services like S3, RDS, and Glue. So, if you’re deep into the AWS ecosystem, this could be your go-to.

Key Features of AWS Redshift

Great Performance: What’s great about Redshift is its performance for the price. We mean, it gives you up to 3x better price-performance than most other cloud data warehouses. That means you get faster results for less, which is pretty awesome when you’ve got a ton of data to process.
Serverless: Redshift Serverless. Seriously, this isn’t just a feature; it’s a game-changer, plain and simple. Imagine never, ever having to stress about fiddling with servers. Never guessing how much compute power you’re gonna need. It just… works. Redshift handles all that scaling for you, automatically adjusting to whatever your data throws at it.
Unified Data Lakehouse: This is where Redshift really starts to sing. It’s got this truly incredible connection with Amazon S3, right? And what that means for you is huge: you can manage both structured and unstructured data, literally all in one spot.
Strong Security: Data security? Redshift’s got you covered. It includes encryption for data both at rest and in transit. Plus, it’s got network isolation and detailed access controls. And with AWS tools like KMS and IAM, your data’s locked up tight and fully compliant.
Generative AI: Chat with Your Data! And for something a bit more cutting-edge? Redshift isn’t just clinging to traditional data warehousing. Nope, it’s stepping boldly into the world of Generative AI. Imagine this: with Amazon Q baked right in, you can actually query your data using plain old natural language.

Snowflake vs AWS Redshift: Key Feature Comparison

Now that we’ve covered the basics of Snowflake and AWS Redshift, let’s compare them side by side based on the most important features that businesses often consider when choosing a data platform.

Performance and Scalability

When you’re picking a data platform, it usually comes down to two things: performance and scalability. Both Snowflake and AWS Redshift are solid, but they go about it differently. So, how do they handle big data and queries that need to run fast?

Snowflake's Performance

Snowflake’s all about flexibility. It splits compute and storage, so you can scale one without messing with the other. You need more storage? Great, go for it. Need more computing power? No problem, just scale that up.

Adaptive Scaling: Snowflake is pretty smart here. If your workload spikes, it automatically adds more power to keep up. When things quiet down, it scales back. Perfect for businesses that have data needs that go up and down all the time.
Concurrency: Snowflake’s got this handled. You know how annoying it is when one person’s query slows everyone else down? With Snowflake, that doesn’t happen. It isolates workloads into virtual warehouses so each team can run their stuff without it affecting anyone else.
Automatic Performance Optimization: No need to manually mess with performance. Snowflake takes care of indexing and clustering automatically, so you don’t have to spend time trying to make things faster.

AWS Redshift's Performance

Redshift is built for big, fast data processing. It uses these things called RA3 nodes, which separate compute from storage, making it more flexible (and easier to scale). You get to scale both compute and storage independently, which is pretty sweet.

RA3 Nodes: So, Redshift just rolled out these RA3 nodes, and honestly, they’re a game-changer. Basically, you can scale compute power without worrying about storage. You get faster queries, and you don’t need a ton of extra resources, which is perfect when you’re dealing with massive data.
Redshift Spectrum: Now, Redshift Spectrum is another thing I love. You can query data that’s chilling in Amazon S3 without moving it into your warehouse first. So you save on storage costs and still get great performance.
Query Performance: Redshift uses columnar storage and compression to make queries go faster. And it runs things in parallel, so it can handle large workloads without breaking a sweat.

Which One is Better for Performance?

If your data is all over the place and you need to quickly scale computing power when things go wild, Snowflake’s probably a better fit. It’s all about flexibility.
But if you’re already in AWS and need something that handles big data like a pro with almost no tuning required, Redshift is probably what you’re looking for.

Security and Compliance

Okay, let’s just get real for a second. If your business handles any kind of sensitive data – and whose doesn’t these days? – then security and compliance are absolutely, unequivocally non-negotiable. We’re not talking about “nice-to-haves” here. These are foundational.

Snowflake's Security

Snowflake has your back when it comes to security at every step, whether it’s storage, access, or anything in between. They’ve got all the security features you’d want, and they meet all the high standards.

End-to-End Encryption: Encryption? Everywhere. All the Time. Seriously, every single piece of data in Snowflake is encrypted. Always. Doesn’t matter if it’s at rest or actively flying around the network. They use the big-league, industry-standard stuff. So, your data? It’s wrapped up tighter than a drum. Protected. Always.
Role-Based Access Control (RBAC): Who Sees What? You Call the Shots. Snowflake’s got this super smart Role-Based Access Control (RBAC) system. Imagine a really strict bouncer for your data. You decide exactly who gets a peek. Only the right people, the ones you specifically allow, can get access. For sensitive info, that’s priceless, right? Keeps things tidy.
Multi-Factor Authentication (MFA): That Extra Lock. Ever use two-factor authentication for your email? It’s like that. So, when someone logs in, it’s not just a password. There’s an extra step. Just another layer. Means only legitimate users are getting in. Smart. Simple. Secure.
Compliance Certifications: They’re All Certified, Baby. Does GDPR make you sweat? HIPAA? PCI DSS? ISO 27001? Snowflake’s got a whole alphabet soup of compliance certifications. They’ve checked all the boxes. Seriously. If your industry has crazy strict rules, Snowflake is probably your best friend.

AWS Redshift's Security

Redshift is no slouch either. If you’re already in AWS, it’s pretty seamless because it integrates with all the other AWS security stuff.

Encryption: Just like Snowflake, Redshift encrypts everything. Data chilling, data moving – it’s all locked down. The cool part? You can even bring your own encryption keys. Talk about control.
Network Isolation: Build Your Own Fort. You want a private little island for your data, completely cut off from the big, scary public internet? Redshift lets you spin up a Virtual Private Cloud (VPC). It’s like building your own digital fortress. Makes it incredibly tough for anyone unauthorized to even sniff your data.
Access Control: IAM Does the Heavy Lifting. For managing who gets in and who doesn’t, Redshift leverages AWS’s Identity and Access Management (IAM). This is huge. It’s robust. It’s flexible. And if you’re already using IAM for other AWS services, it’s just… familiar. Easy peasy.
Compliance Certifications: Redshift’s also certified for SOC 1, SOC 2, SOC 3, HIPAA, PCI DSS, and GDPR.

So, Which One’s Better?

Honestly, both are solid. If you need really tight control, especially with features like RBAC and MFA, Snowflake’s a good pick. It’s ready to go with strong security built right in.

But hey, if you’re already deeply embedded in the AWS universe, and you need something that just sings with all your existing AWS services? Then Redshift? It’s literally a no-brainer. It just slips right in. Seamless. No fuss, no extra setup headaches, nothing. It’s like it was built just for you, fitting right into your current cloud setup without skipping a beat.

Snowflake vs AWS Redshift: Pricing

Snowflake’s Pricing

Snowflake’s pricing is pretty straightforward with a pay-as-you-go setup.

Compute: You literally only pay for what you actually use. It’s billed by the second, based on your active usage time. So, no sneaky overcharges. You’re never paying for idle time, which is, frankly, brilliant for managing costs.
Storage: This is charged separately, yeah, but here’s a cool perk: Snowflake automatically compresses your data. What does that mean for your wallet? You end up paying way less for storage than you might expect. Smart.
Cost Optimization: They give you the reins here. You can effortlessly scale up or down to match your fluctuating needs. Plus, there’s a super intuitive interface that lays out exactly what you’re consuming, making cost management genuinely simple. You can see your usage patterns and tweak things on the fly.

AWS Redshift’s Pricing

Redshift handles its charges a bit differently. It primarily bills you based on the number of nodes you’re running or the serverless compute you consume.

Pricing Options: You’ve got choices here: on-demand or reserved pricing. On-demand? That’s your flexible friend – pay for what you use, when you use it. But if you’re ready to commit for a longer haul, reserved pricing can seriously save you a good chunk of change. It’s all about finding that sweet spot for your commitment level.
Storage Savvy: How Redshift charges for storage really boils down to the kind of storage you opt for. But, here’s a tip for keeping costs down: using RA3 nodes combined with Redshift Spectrum can make storage incredibly cheap. Why? Because it cleverly stores most of that data directly in Amazon S3, leveraging S3’s low costs.

Which Platform Offers Better Pricing?

Honestly, there’s no single “better” answer here; it truly depends on your operations.

Snowflake really shines for businesses with unpredictable or highly variable workloads. Its pure pay-per-use model means you’re never stuck paying for capacity you don’t need.
AWS Redshift is better for businesses within the AWS ecosystem, offering both traditional and serverless pricing options.

Conclusion: Which One Should You Choose?

Alright, final thoughts time. Both Snowflake and AWS Redshift are absolute powerhouses, fantastic choices in the data platform arena.

Go with Snowflake if you need flexibility across clouds, want easy data sharing, and like the idea of built-in machine learning. Plus, if you want to pay as you go and scale as needed, Snowflake’s perfect.

Pick AWS Redshift if you’re already using AWS and need fast analytics or have predictable workloads. It’s a great fit for businesses that are fully in the AWS world and need fast processing with minimal fuss.

Both platforms are solid, your choice comes down to your cloud strategy and how your workloads play out. If you still need help in picking the right data platform for your business, feel free to reach out to our cloud experts at Techtic Solutions.

FAQs

Q: What is the difference between Snowflake and AWS Redshift?

The main difference lies in architecture and cloud support. Snowflake separates compute and storage with native multi-cloud support (AWS, Azure, GCP), while AWS Redshift is primarily for AWS users, offering tight integration with Amazon services. Snowflake also offers zero-copy cloning, easier data sharing, and flexible pay-per-use pricing.

Q: Is Snowflake better than Redshift for big data analytics?

Snowflake is often preferred for big data analytics when flexibility and cross-cloud compatibility are required. Its scalable compute, automatic optimization, and native support for AI/ML workloads make it ideal for diverse data use cases. Redshift performs well within AWS, especially for structured data at high speed.

Q: Which is more cost-effective: Snowflake or Redshift?

Snowflake offers a pure pay-per-use model with second-based billing, which is great for variable workloads. AWS Redshift can be more cost-effective for predictable workloads using reserved pricing. The best option depends on your usage pattern, cloud strategy, and long-term needs.

Q: Does Snowflake support AWS, Azure, and Google Cloud?

Yes, Snowflake is a multi-cloud platform that runs seamlessly across AWS, Microsoft Azure, and Google Cloud. It enables cross-cloud data sharing and replication, making it highly flexible for hybrid or multi-cloud strategies.

Q: Which data warehouse is better for AI and machine learning?

Snowflake is better suited for AI and ML if you’re using Python-based tools via Snowpark and need integrated data pipelines. AWS Redshift integrates with SageMaker and Amazon Q for generative AI, making it a strong contender if you’re already in the AWS ecosystem.