2024 Snowflake Summit introduced Snowflake Unistore Hybrid Tables, a groundbreaking innovation alongside Apache Iceberg and Snowpark enhancements.
What is Unistore?
Unistore is a new workload that unifies transactional and analytical data in a single platform, eliminating the need to move data across systems or maintain redundant datasets. While Snowflake originally focused on analytical workloads, Unistore extends these capabilities to transactional processes.
The Benefits of Unistore
• Unified Data Environment: Integrate analytical and transactional data in one location
• Simplified Development: Build transactional applications handling enterprise-scale data
• Eliminated Silos: Run analytical queries in real-time on transactional data
• Consolidated Systems: Standardize governance and security controls
The Problem Unistore Solves
Traditionally, transactional and analytical workloads have had fundamentally different characteristics:
Transactional Workload | Analytic Workload |
Response time in sub-second | Response time in seconds to minutes or longer |
Run the business | Analyze the business |
Thousands of concurrent users | Tens to hundreds of concurrent users |
Concurrency of 1,000-10,000 queries per second | Concurrency of 10-200 queries per second |
1-2 rows processed | Millions of rows scanned |
While transactional systems typically handle very short, fast updates to individual rows with transaction completion averaging 50 milliseconds, most analytic queries process billions of rows, taking seconds to minutes to complete.
This separation has historically led to several challenges:
• Complexity: Organizations need to stitch together multiple disparate technologies from
different vendors.
• Extract, Transform, and Load (ETL) Overhead: Periodic extractions, loads, and data
transformations are required to produce useful insights from analytical systems. These
data pipelines are often complex, fragile, and expensive to maintain.
• Latency: Despite best efforts to produce near real-time data loading and automated
pipelines, there's inherent latency in extracting and loading data to analytics platforms.
• Data Silos: Workload separation often leads to further complexity in blending operational
and analytical data.
Hybrid Tables
Hybrid Tables power Unistore with fast, single-row operations, featuring:
• Required primary keys with enforced uniqueness
• Indexes for accelerated lookups
• Referential integrity through foreign key relationships
• Row-level locking with Read Committed isolation
These tables deliver a new database processing engine supporting both workloads at scale, enabling sub-second transaction processing with concurrency up to 10,000 queries per second.
Bridging the Workload Gap
Traditional separation between transactional and analytical systems created challenges:
• Complex integration of disparate technologies
• ETL overhead and pipeline maintenance
• Inherent latency in data processing
• Data silos complicating operations
Unistore addresses these by allowing transactional systems to deploy directly on Snowflake without separate platforms, significantly simplifying architecture.
Market Perspective
Recent research shows 82% of enterprises consider unified transactional and analytical workloads a strategic priority. Organizations implementing such platforms report 30% reduction in ownership costs and 45% improvement in time-to-insight.
Snowflake's Unistore represents a fundamental shift in data platform evolution, breaking the 40-year tradition of separating these workloads and positioning organizations for more efficient data-driven operations.
