Why We Bet on Snowflake (And Why You Might Want to)

By J. T. Taylor, Founder & CEO

Last updated: August 8, 2025

Snowflake has the features enterprises need for modern high-performance workloads in the cloud

At TMS, when we evaluate data platforms for our clients, we often come back to the same question: Why does managing data still feel so fragmented, slow, and painful? I’ve seen brilliant teams get bogged down by rigid systems, unpredictable costs, and endless tuning. So we went hunting for something better.

That search led us straight to Snowflake. And once we dove in, the difference was night and day.

This post isn’t just a list of features — it’s a look at how Snowflake stacks up against the competition and why we chose it as the backbone of our modern data solutions. From scalability to security, AI readiness to cost control, Snowflake isn’t just “another option” — it’s the platform we trust to power the future.

Snowflake Advantages at a Glance:

Feature	Snowflake	Traditional Databases
Cloud-native	✅ Yes	❌ Often retrofitted
Infinite scalability	✅ Yes	❌ Limited or costly
Multi-cloud support	✅ AWS, Azure, GCP	❌ Usually single-cloud
Zero copy data sharing	✅ Yes	❌ Manual or complex
DataOps + CI/CD ready	✅ Yes	❌ Rarely
Seamless AI integration	✅ Yes	❌ Requires external tooling
Built-in security & governance	✅ Yes	❌ Fragmented or complex
Pay-per-second billing	✅ Yes	❌ Static pricing or overprovisioned

Snowflake vs. the Competition

Snowflake stands apart from both legacy data stacks and modern cloud-native competitors. While platforms like Databricks, Amazon Redshift, Google BigQuery, Dremio, and Azure Synapse each offer specialized features, Snowflake delivers a unified, easy-to-use platform that combines the best of data warehousing, data lake architecture, and secure data sharing—with near-zero management overhead. Even so, a few AWS-native patterns lean toward Redshift (called out below).

Database	✅ Pros	❌ Cons
Databricks	Great for ML	requires Spark expertise and lacks native data governance features Snowflake delivers out-of-the-box
Redshift	AWS-native: Lake Formation/Glue governance; Spectrum over S3; streaming from Kinesis/MSK; federated queries to Aurora/RDS; PL/pgSQL reuse.	AWS-only; some features need extra AWS service setup/quotas; benefits from workload-aware tuning (automation has improved).
BigQuery	Optimized for batch analytics	unpredictable pricing and limited governance compared to Snowflake
Dremio	Offers SQL over lakehouse data	lacks the robust ecosystem, scalability, and security compliance of Snowflake
Azure Synapse	Strong Microsoft integration	more complex setup and slower innovation cycles than Snowflake

When Redshift can make sense (AWS-only shops)

Lake Formation + Glue policies must apply uniformly across Athena/EMR/Redshift.
“Must run in our VPC.” Redshift lives in your AWS account/VPC; Snowflake connects via PrivateLink.
Native streaming & federation. Kinesis/MSK streaming and federated queries to Aurora/RDS with AWS IAM/VPC.
Heavy PL/pgSQL reuse. Large existing PostgreSQL procedure codebases.

For everything else—multi-cloud optionality, unified UX, minimal ops, global data sharing, and rapid AI features— we pick Snowflake.

Snowflake wins on simplicity, performance, flexibility, and integrated governance — without locking you into a single cloud provider or requiring you to stitch together tools.

At the end of the day, we chose Snowflake because it doesn’t make us choose — between performance and simplicity, between innovation and governance, or between scaling fast and staying secure. It just works.

Let’s connect!

Your Snowflake journey starts here. Reach out now to discover how Snowflake can transform your data strategy — and how TaylorMade can get you there faster.

TaylorMade Software, Inc. is a Snowflake-certified consultancy with deep experience across industries. Whether you’re just starting or optimizing, we make Snowflake work for you.

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