5 reasons why MySQL HeatWave on OCI is better than Snowflake

Here are the top five reasons to choose MySQL HeatWave on Oracle Cloud Infrastructure (OCI) over Snowflake.

  1. Simplicity: MySQL HeatWave enables transactions, real-time analytics across data warehouses and data lakes, and machine learning in one cloud database service, without extract, transform, and load (ETL) across cloud services.

  2. Lower cost: MySQL HeatWave provides 15X better price-performance than Snowflake and MySQL HeatWave Lakehouse provides 19X better price-performance.

  3. Higher performance: MySQL HeatWave is 4X faster than Snowflake. The query performance of MySQL HeatWave Lakehouse is 18X faster than Snowflake, and the load performance is 2X faster than Snowflake.

  4. Machine learning–powered automation: MySQL Autopilot provides workload-aware, machine learning–powered automation of various aspects of the application lifecycle, including provisioning, data loading, query execution, and failure handling.

  5. Increased data protection: MySQL HeatWave eliminates the risk of data movement between data stores and provides advanced security features to protect data throughout its lifecycle and support compliance with regulatory requirements.


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"You can spend $80K on HeatWave and that would cost you $420K to run on Snowflake. It’s a no-brainer."

Patrick Moorhead
Founder and CEO, Moor Insights & Strategy


1. Simplicity


Capability and Evidence
MySQL HeatWave
Snowflake
One cloud database service for OLTP and OLAP across data warehouses and data lakes
yes

Customers can run both OLTP and analytics workloads across data warehouses and data lakes in a single cloud database service—without changes to existing MySQL applications.
no

Snowflake is designed only for analytics workloads. Customers can't run rich and mature OLTP workloads directly on Snowflake. Snowflake’s Unistore is only in private preview.
No ETL duplication
yes

The complex, time-consuming, and expensive ETL is eliminated.
no

An ETL process is required to move data from OLTP sources to Snowflake.
Real-time analytics
yes

Queries always access the most up-to-date data; there’s no data transfer between databases.
no

By the time data goes through ETL and is available in Snowflake, it’s already stale.
In-database machine learning
yes

With HeatWave AutoML, developers and data analysts can build, train, deploy, and explain machine learning models within MySQL HeatWave. Data and ML models don’t leave the database, which speeds up results and prevents the risks of data movement between data stores.
no

With Snowflake, users must rely on third-party machine learning tools or publicly available libraries to build, train, and deploy ML models. Snowflake doesn’t provide in-database machine learning.
Automated machine learning lifecycle
yes

The ML lifecycle is fully automated, including algorithm selection, intelligent data sampling, feature selection, and hyperparameter tuning for all model types.
no

Snowflake doesn’t support automated, in-database machine learning.
Explainable data models and predictions
yes

All models and predictions are explainable, increasing trust, fairness, causality, and repeatability and helping with regulatory compliance.
no

Snowflake doesn’t provide in-database machine learning with built-in explainability.

2. Lower cost

MySQL HeatWave provides 15X better price-performance than Snowflake, as demonstrated by a 10 TB TPC-H benchmark.

Cost comparison chart, details below
Cost comparison: 10 TB TPC-H
Service Cost
MySQL HeatWave (10 nodes) $34,073
Snowflake (X-Large cluster)) $280,320

Note: Savings can be greater with MySQL HeatWave since this comparison doesn’t consider that with Snowflake you need to pay for a separate OLTP database, such as Amazon Aurora, and for the data transfer between the two databases—which you can avoid with MySQL HeatWave.

MySQL HeatWave Lakehouse provides 19X better price-performance.


Capability and Evidence
MySQL HeatWave
Snowflake
Real-time elasticity to any number of nodes
yes

Customers can increase or decrease the size of their HeatWave cluster by any number of nodes without incurring any downtime or read-only time. Data is automatically rebalanced among all available cluster nodes for high performance.
no

Snowflake provides compute resources only in building blocks of 1, 2, 4, 8, 16, 32, 64, 128, 256, and 512 nodes. Customers have no option but to overprovision their deployment by choosing a larger size than needed, spending more money than necessary. For example, scaling up from 32 nodes requires jumping to 64 nodes, even though only a small increment of compute resources may be needed.

3. Higher performance

As demonstrated by a 10 TB TPC-H benchmark, MySQL HeatWave on OCI is 4X faster than Snowflake.

Query performance chart, details below
Query performance: 10 TB TPC-H
Service Average execution time in seconds (Geomean)
MySQL HeatWave (10 nodes) 14.23
Snowflake (X-Large cluster)) 47

As demonstrated by a 500 TB TPC-H benchmark, the query performance of MySQL HeatWave Lakehouse is 18X faster than Snowflake, and the load performance of MySQL HeatWave Lakehouse is 2X faster than Snowflake.

Query performance chart, details below
Query performance: 500 TB TPC-H
Service Average execution time in seconds (Geomean)
MySQL HeatWave Lakehouse (512 nodes) 47
Snowflake (4X-Large cluster)) 821
Load performance chart, details below
Load performance: 500 TB TPC-H
Service Load time in hours
MySQL HeatWave Lakehouse (512 nodes) 4.43
Snowflake (4X-Large cluster)) 9.04

4. Machine learning–powered automation


Capability and Evidence
MySQL HeatWave
Snowflake
Automated provisioning of the optimal cluster size
yes

MySQL Autopilot uses machine learning to automatically provision the optimal cluster size for a given data set, whether the data resides in MySQL or in the object store.
no

Developers and DBAs must guess or manually estimate by trial and error the optimal size of the cluster.
Automated query performance tuning
yes

MySQL Autopilot learns from the execution of queries and uses machine learning to automatically improve the performance of subsequent, different queries.
no

Query plans aren’t automatically improved using machine learning models.
Automated schema inference
yes

MySQL Autopilot automatically infers the mapping of the file data to data types in the database, including for CSV file formats, by intelligently sampling portions of files in the object store.
no

Snowflake can’t infer the mapping of the file data to data types in the database for CSV files.
Automated data loading
yes

MySQL Autopilot analyzes the data in the object store to predict the load time into the in-memory HeatWave cluster and automatically loads the data.
no

Snowflake doesn’t provide a data load time capability.

5. Increased data protection


Capability and Evidence
MySQL HeatWave
Snowflake
No ETL process
yes

The risk of data movement between data stores is eliminated.
no

Data security and regulatory compliance risks can increase as data moves between separate services for OLTP, OLAP, and ML.
Digital signatures to confirm the authenticity and integrity of messages
yes

Built-in server-side asymmetric encryption with key generation and digital signatures is provided.
no

Built-in server-side asymmetric encryption to implement digital signatures isn’t provided.


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