Snowflake Hybrid Tables: Enhancing Transactional and Operational Workloads

Snowflake is already a feature-rich platform that offers numerous advantages over competing technologies, such as its independent scalability of storage and compute and its security and encryption. Now, Snowflake is in the process of introducing Hybrid Tables into its architecture. Hybrid Tables are a new Snowflake table type that has been optimized for both transactional workloads and operational workloads.

Note: Hybrid Tables are currently a preview feature, available only to accounts in select AWS regions, excluding trial accounts.

What are Hybrid Tables?

Previously, Snowflake stored all table data in columnar format using micro-partitions to store and organize the data. This method of data storage is particularly useful for lowering storage costs, as columnar data achieves higher rates of compression than row-oriented data. There are some disadvantages to this storage method, one of those being that it doesn’t lend itself to great performance when dealing with truly transactional workloads. However now with Hybrid tables, you can store your data in a way that lends itself to much better performance on transactional workflows that involve a high level of concurrency.

Architecture and Integration

A key benefit of Hybrid Tables is that they can seamlessly integrate into an existing database. Hybrid tables do not require any special Snowflake database to store their data, or a special virtual warehouse to query them. In fact, you can even join Hybrid Tables with other Snowflake tables as well as execute atomic transactions across Hybrid Tables and other Snowflake tables.

These tables are different both in function as well as architecture when compared to standard Snowflake tables. For example, while standard Snowflake tables store information in columnar format micro-partitions, Hybrid Tables use a row store as the primary data store to provide enhanced operational query performance.

When you write to a Hybrid Table, the data is written directly into the row store. Data is then asynchronously copied into object storage. This approach provides better performance and workload isolation for large scans without affecting ongoing operational workloads.

Hybrid tables also implement row-level locking, as opposed to the partition or table locking used in standard tables. This allows for better concurrency in transactional workloads.

Advantages and Disadvantages of Hybrid Tables in Snowflake

Hybrid Tables are a powerful tool, but it is important to consider the advantages and disadvantages they offer when compared to a standard Snowflake table to determine whether it’s suitable for your use case.

Advantages:

• Optimized for hybrid transactional and operational workloads with low latency and high throughput on small random point reads and writes
• Supports enforced unique and referential integrity constraints (PRIMARY KEY, FOREIGN KEY, and UNIQUE)
• Seamless integration with existing Snowflake architecture, allowing joins and atomic transactions with standard tables
• Row-level locking for better concurrency in transactional workloads
• Improved performance for high-concurrency random reads and writes

Disadvantages:

• Typically has a larger storage footprint due to row-oriented primary storage
• Potentially higher storage costs compared to columnar storage
• Less efficient for large analytical queries and wide-range scans
• Limited availability (only in select AWS regions, excluding trial accounts)
• Requires a PRIMARY KEY constraint, which may necessitate data model adjustments

Use Cases

Hybrid Tables are particularly useful in the following scenarios:

• Building cohorts for targeted marketing campaigns through interactive user interfaces
• Maintaining central workflow states to coordinate large parallel data transformation pipelines
• Serving precomputed promotion treatments for users visiting websites or mobile apps
• High-concurrency operational workflows requiring frequent small updates and retrievals of entire records
• Applications needing a balance of transactional integrity and analytical capabilities within a single platform

Hybrid Tables Keep Snowflake on the Cutting Edge

Snowflake’s introduction of Hybrid Tables significantly enhances its platform, offering a versatile solution for various workloads. With their unique design and easy integration, Hybrid Tables boost performance and efficiency, making them a valuable tool for businesses looking to optimize data management. While they come with some trade-offs, such as larger storage needs and potentially higher costs, the benefits make Hybrid Tables a compelling option for many applications. As Snowflake evolves, features like Hybrid Tables ensure it stays at the cutting edge of data warehousing and analytics.

Find out how your organization could benefit from implementing Hybrid Tables. Contact 7Rivers to start a conversation.