Snowflake Data Cloud Driving Innovation with Unistore Hybrid Tables
This year’s Snowflake Summit brought us a step closer to the next phase of innovation with its all-inclusive and progressive feature additions. Along with Apache Iceberg, and Snowpark, the world also became a witness to another interesting feature launch – Snowflake Unistore Hybrid Tables.
For the last four decades, the data has been stored independently in silos using Online Transaction Processing Systems (OLTP) in order to support transactional and analytical workloads. You get a single unified platform in the form of Snowflake Unistore Hybrid Tables to store and process massive amounts of transaction and analytic workloads.
Understanding Snowflake Unistore Hybrid Tables
Years after years, independent transactional and analytical databases dominated the IT landscape, considerably limiting the growth of a business. But with Unistore, Snowflake has completely changed the data management and analytics game. This single database platform marks the shift in database technology by merging both the data together in near-real-time.
Removing data silos also enabled enterprises towards faster analytics on large-scale data and drive businesses to become data-powered companies.
Different workloads with distinctive features – Transactional and Analytical
An IT system can be divided into transactional (OLTP) and analytical (OLAP), where the former provides source data to data warehouses while the latter analyzes it.
The below table helps you understand how different transactional workload is from analytical processing. Check out the factors that separate them.
In other words, though both the systems seem similar and can be categorized under the online processing systems, OLTP is more online service-oriented (SOA) and OLAP is a research-oriented architecture. They act as a support system for each other.
Drawbacks of traditional transactional and analytical workload architectures
Apart from being a complex and costly solution, traditional transactional and analytical platforms gave birth to various concerns.
Complex arrangement with data silos: The independent systems made it tough for architects to merge multiple disparate technologies from different vendors under one roof. As a result, operational and analytic data remained separate, limiting their use in unison.
Extract, Transform, Load (ETL): Architects and analysts needed to perform periodic data integration processes to retrieve valuable insights from the analytic systems. These data pipelines are often complex, fragile, and expensive.
Latency: The system was not able to produce near real-time data loading and automated pipelines. The in-built latency during extracting and loading data to the analytics platform delayed the process.
Addressing OLAP-OLTP challenges with Snowflake Unistore Hybrid Tables
Snowflake’s scalable solution to analytic workloads is now extended to transactional workloads with Unistore while Hybrid Tables ensures the delivery of an entirely new database from scratch that supports both kinds of workloads. This new addition results in low latency lookups, high concurrency workloads, and enforcement of primary and foreign key constraints for referential integrity. This addition came with other impressive features, such as cloning, time travel, user-defined functions, and streams.
This is how you can create a hybrid table:
Your business can get the benefits of Unistore and Hybrid Tables, which includes:
Standardize set of data governance and security controls under one roof, including Tagging and Dynamic Masking.
Get a unified dataset for all your transactional and analytical data to build better customer experiences and draw new business insights.
Scale up your data warehouse dynamically to accommodate larger workloads.
Adopt additional Snowflake features, such as Time Travel, Zero Copy Clones, and more.
Breaking the continuity of the past 40 years, Snowflake has successfully merged transactional and analytical data into one platform. The two entirely opposite solutions can now perform a transactional query in a period of milliseconds with a high concurrency of up to 10,000 queries per second. This is how Snowflake delivered and improved its best solution with Unistore Hybrid Tables.
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