With time, the volume, velocity and variety of data keep increasing. Nowadays, any business needs a single source of truth for its operations backed by data pipelines anywhere, anytime. The traditional on-premises data warehouses struggle to meet business needs. That’s where cloud data warehousing comes in.
With cloud data warehouses, data integration is not merely collecting data from disparate sources. Cloud data warehousing also include data readiness, migration, data management and data warehouse automation. The key is choosing the right data integration platform and tool to maintain and grow an organization’s business.
Snowflake is a cloud data warehouse available as software-as-a-service (SaaS). It has a pay-as-you-go model. Snowflake can be hosted on cloud platforms such as AWS, GCP and Azure. In Snowflake’s architecture, cloud services, storage and computing are separate layers. So, one can run multiple workloads in parallel with no resource contention.
Snowflake data warehouse separates compute from storage. Hence, data loads can continue to run on virtual warehouses without interfering with business users who are retrieving data for reporting purposes. Snowflake, an elastic cloud data warehouse, automatically scales up and down according to your needs. That’s how the platform strikes a balance between performance and cost. supports a multi-cluster meaning it can add resources to manage user and query concurrency needs during peak hours. All these solve the resource contention limitations of a traditional data warehouse.