With its columnar format and unique features, we know that the Snowflake Data Cloud is fantastic at analytical workloads. But what if Snowflake could handle transactional data as well? What insights could you derive from having your transactional and analytical data in one place? That’s exactly what Snowflake aims to achieve with their new feature: Hybrid tables.
In this blog, we’ll go over what Hybrid tables are, how they differ from standard Snowflake tables, and some real-world scenarios where using Hybrid tables in your Snowflake account would be beneficial.
What Are Snowflake Hybrid Tables?
Hybrid tables are a new table type in Snowflake that enables fast, single-row operations. This lets teams develop lightweight transactional use cases like serving data or storing an app’s state — all within Snowflake.Â
Unlike standard Snowflake tables, Hybrid tables enforce unique constraints for required primary keys and include indexes to retrieve data faster. Enforcing the primary keys also allows the use of referential integrity constraints to better define the relationship between primary and foreign keys.Â
Hybrid tables can be used alongside standard tables to combine transactional and analytical data to create deeper insights into your business.
This concept vastly differs from Snowflake standard tables, which are built primarily for analytical use. Because of this, the feature has been in private preview since it was announced nearly two years ago.Â
However, it is now available in public preview in specific AWS regions, excluding trial accounts.
What Workloads Do Snowflake Hybrid Tables Support?
The real benefit of utilizing Hybrid tables is that they bring transactional and analytical data together in a single platform. This creates a plethora of possibilities for workloads within Snowflake, enabling you to manage operational data and perform ad-hoc analysis on the same platform.Â
Here are some real-world examples of what Hybrid tables could be used for:
E-Commerce Fraud Detection: In an e-commerce application, you might use a hybrid table to store real-time transaction data (purchases, logins, etc.). This allows for quick fraud checks while enabling analysis of historical fraud patterns to improve detection models.
Customer Relationship Management (CRM): A CRM system could leverage Hybrid tables to store customer interactions (calls, emails, etc.), enabling real-time agent visibility while allowing for customer segmentation and behavior analysis to personalize marketing campaigns.
Internet of Things (IoT) Sensor Data: For ingesting and managing sensor data from IoT devices, Hybrid tables can handle the high volume of real-time updates while enabling historical analysis of sensor readings to identify trends or predict equipment failures.
Financial Services Trade Processing: In trade processing systems, hybrid tables can efficiently manage trade orders (inserts, updates) while allowing for real-time risk calculations and historical analysis of trading patterns to identify opportunities.
Supply Chain Management: A supply chain application can benefit from Hybrid tables by tracking inventory levels and movements in real time while enabling analysis of past demand patterns to optimize inventory allocation and predict shortages.
These are just a few examples, and the suitability of Hybrid tables depends on your specific needs.Â
The key takeaway is that Hybrid tables excel in scenarios requiring real-time operational data management and the ability to analyze that data for deeper insights.
Why Choose phData to Help Implement Hybrid Tables?
When businesses want to utilize a newly released feature like Hybrid tables, it can be challenging as there won’t be much information available about implementation nuances and best practices surrounding the feature.Â
As an Elite consulting partner of Snowflake and their 2023 Partner of the Year, phData gets early access to new Snowflake features. We can test-drive these features and determine how to leverage them for our clients best well before they reach public release. This helps ensure our clients are using the latest and greatest features from Snowflake to their optimal potential.Â
Additionally, phData has the knowledge and experience of dozens of engagements involving Snowflake that we leverage to help our clients utilize everything they offer. Not only can phData provide development resources to aid your business, but we can also provide analytics engineers to derive insights from your data, visualization developers to create front-end facing applications, and our Elastic Platform Operations can ensure that your environment runs smoothly and continues to in the future.
Closing
Snowflake’s Hybrid tables are a powerful new feature that can help organizations break down data silos and bring transactional and analytical data together in one platform. Hybrid tables can streamline data pipelines, reduce costs, and unlock deeper insights from data.Â
If you’re looking to improve your organization’s data management capabilities, Snowflake Hybrid tables are definitely worth considering!
FAQs
Since they are very different from Snowflake’s standard tables and are still in a preview state, not all Snowflake features are available for Hybrid tables. Most notably, Time-Travel, Fail-Safe, and Cloning are unavailable, among other features.
Although virtual warehouse consumption is the same when querying Hybrid tables as it is for standard tables, Hybrid table storage is more expensive than traditional storage. Additionally, there are charges for Hybrid table requests as the tables consume additional credits as it uses serverless resources on the underlying row storage clusters. Your consumption of serverless resources is measured based on the amount of data that is read from or written to storage clusters.
