6 Essential Features for Enterprise Data Platforms: An Insight

In today's digital age, the growth and success of an enterprise heavily rely on how it manages and leverages its data. There are multiple enterprise data platforms in the market, each offering its distinct capabilities. However, when it comes to enterprise-grade requirements certain key features are indispensable. In this blog post, we will delve into six such capabilities – comprehensive cross-cloud replication, zero copy database and schema clone, collation support, stored procedures, multi-table transactions, and transparent online upgrade – that every enterprise must consider while choosing their data platforms.

In the modern data ecosystem, a comprehensive cross-cloud failover strategy is critical for maintaining uninterrupted operations. What makes it truly effective? First, it’s not just about the replication of an account’s data, but a full replication of role-based access control, governance policies, compute resources, network policies, integrations with identity, and other essential account entities. Second, the replication service can automatically scale based on replication demand to ensure timely data replication even as replication data volume increases. Finally, replication is easy to configure and deploy. Snowflake offers such an advanced replication mechanism that can be set up with just a few SQL commands in minutes. When using data platforms that don't support comprehensive cross-cloud replication, customers have to build custom solutions which lead to longer deployment cycles and a significantly higher total cost of ownership. 

This advanced replication strategy goes beyond ensuring operational continuity; it plays a critical role in establishing cross-cloud data governance. For geographically distributed teams that use different cloud vendors, Snowflake allows the governance policies to be defined in one central place. When data moves to different regions or clouds, the governance policies are consistently applied without additional work. 

Furthermore, we have seen several evolutions in organizations’ cloud strategies, often driven by events such as executive realignments, or acquisitions and mergers. Given these dynamics, choosing a data platform that provides a holistic cross-cloud replication solution not only meets today’s need but is also a future-ready decision, ensuring a seamless and disruption-free transition between cloud vendors when the need arises.

In the realm of enterprise operations, the capability to rapidly clone a database or a schema is critical. A cloned environment can serve as a virtual Dev, QA, and UAT environment which allows you to do DevOps on your production Snowflake account.  This can also be a sandbox for testing, a temporary workspace for development, or a recovery fallback for disaster management. Any delays in the process could impede the efficiency of these activities and lead to business disruptions. Thus, a quick and efficient cloning process is an important feature to have in any data management solution.

Snowflake's zero copy clone and time travel features bring about an almost magical transformation to the data management process. The zero copy clone feature allows users to instantaneously clone an entire database, schema, or table, without the storage footprint and cost of actually copying the base data. Combined with the time travel feature, users can create a database or schema clone that points to a specific timestamp in history, providing an unrivaled level of flexibility and control over data. This is a powerful capability for enhancing business operations, reducing delays, and boosting productivity.

Collation is a critical aspect in data platforms that deals with the accurate sorting and comparison of strings. It can be based on locale, case-sensitivity, accent-sensitivity, punctuation-sensitivity, first-letter preference, case-conversion, and space-trimming. Collation support is vital for businesses as it ensures string data aligns with business rules and cultural contexts.

When using data platforms that don't support collations, data might be sorted or compared incorrectly, leading to inaccurate results, difficulty in migration and inefficient operations. For instance, the comparison of 'i' and 'I' under a case-insensitive en_US locale will result in them being treated as identical. However, in the context of a case-insensitive tr_TR locale, they will be considered different. Companies operating in different countries would require locale-specific collation to handle data according to each region's language. Thus, robust collation support is essential to ensure that business reports and dashboards are accurate and remain consistent especially during the migration process.

Stored procedures refer to programs stored directly in the database, which can be reused over time. They have been an essential component for programmatically controlling data operations, a requirement often specified by various ETL, reporting, and analytics tools used in businesses. While stored procedures are typically written in SQL, they can also be written in other languages such as JavaScript, Python, Java, and Scala.

Stored procedures offer a multitude of advantages. They provide performance enhancement by bringing your data manipulation logic closer to your data, resulting in faster execution times. They ensure data integrity and security by setting up safeguards that prevent unauthorized data access and modifications. In addition, the modularity of stored procedures helps to ward off redundancy and promote consistency in your codebase.

Using data platforms that lack stored procedure support can pose challenges during data migration as it often necessitates rewriting substantial portions of code and scripts, a process that can be both time-consuming and error-prone. Hence, an enterprise data platform should support stored procedures for both the functional benefits and ease of migration.

A multi-table transaction allows for changes to be made across multiple tables as a single, atomic operation. In enterprise-level operations, data is often distributed across various tables, and maintaining data consistency is crucial. Multi-table transactions ensure that either all changes are committed successfully, or none are, thereby preventing partial updates that could lead to data inconsistency. This is essential in situations like inventory management, where changes in one table must reflect in others simultaneously to maintain accurate stock counts. Hence, multi-table transaction support allows enterprise-grade data platforms to fulfill the complex needs of enterprise applications.

Enterprises require data platforms that guarantee operational continuity, even during release updates. Any downtime could lead to significant operational disruption, financial losses, and reputational damage. Unlike some data platforms where it is the customers’ responsibility to restart their clusters on a regular basis to have the latest maintenance updates, Snowflake’s worry-free release updates makes it transparent to customers. This distinction enables businesses to benefit from the latest updates and features without compromising system availability and service delivery.

Selecting a data platform for an enterprise is a critical task that requires a careful evaluation of several features. Comprehensive cross-cloud replication, zero copy database and schema clone, collation support, stored procedures, multi-table transactions, and transparent online upgrade are indispensable features for any enterprise-grade data platform. These features ensure the platform can handle complex business requirements, facilitate efficient data management, and guarantee continuous operations, all of which are pivotal for the growth and success of an enterprise. 
If you’re looking for a modern data platform that includes these features, learn more about the Snowflake Data Cloud, and how organizations like AT&T, Pfizer, Bumble, and AMNHealthcare use Snowflake to manage their data today.