How Snowflake tackled limitations of legacy data warehouses

10.02.2020

Cloud data warehousing emerged as an answer to recognizing the limitations of conventional data warehouses. Most of the companies are realizing the importance of shifting their legacy to cloud. Let’s explain why this is happening now and how it differs from the on-prem data warehouse.

Not so long ago, the only data businesses collected was written down manually. The scale and growth of data was predictable and therefore it was easy to foresee the size and functionality of the needed warehouse. Still, you needed the hardware, server rooms and operational costs to maintain it.

  1. With Snowflake, you pay for the compute and storage you actually use. No upfront capex investment.

The digital world changed the volume, types and sources of data businesses are receiving. Websites, mobile phones, machines, sensors, applications – and the list goes on. This kind of data is using semi-structured languages (data that’s difficult to track in a fixed format) as opposed to SQL. Because they were so different, they were difficult and time consuming to integrate with the data coming from internal sources, which used some form of SQL – the standard and structured language used for storing data.

  1. With Snowflake, you can easily store, transform and analyse structured and semi-structured data together.

Aside from that, business world experienced a rapid adaptation of SaaS – like CRM and ERP software suites, online marketing tools, etc., which uses storage on cloud. Same goes for machine generated data that originates outside of company’s data centres. All of the above started arriving in unpredictable and fast-growing volumes. Conventional data warehouses were simply not fit for the task of processing this rising volume and complexity of the new data, so it caused the analysis to hang or even crash the system.

  1. Snowflake was designed to handle any data volume at blazing speed and virtually unlimited scale.

The other problem was that with majority of the data now stored in the cloud, it was time consuming and expensive to pull it inside your data centre.

  1. The natural place for integrating data became the cloud, so the next logical step was to build warehouse in the cloud. Snowflake designed and implemented a new, unique architecture to stay clear from the limitations of existing solutions – it was built from the ground up for the cloud.

Demand for data access and analytics increased dramatically. It used to be reserved for the selected few in the company, but now data driven decisions have become a part of almost every operational aspect in the organisation. To stay competitive in business world today, companies need to track data in real time to provide critical business insights. This leads us to two things, required for process to function – concurrency and scalability. On legacy, concurrency is limited – users and applications are fighting for limited resources.

  1. Concurrency at Snowflake is unlimited. Scale to as many users you like.

The number of needed queries most companies are having today, would significantly slow down or even made the old systems to crash. This means more time and money needed to be invested in order to maintain the systems. Those were, rather than being a helpful tool, becoming an obstacle on the way to a data driven insight.

  1. Snowflake’s on demand, elastic scalability of a cloud-based data warehousing provides the flexibility and adaptability to preform multiple queries without slowing down other workloads.

Growing trend is to build analytics into business applications (as opposed to analytics operating as a separate entity), yet researches show that majority is still not using advanced analytics in their data practices, but are instead still spending their time with building overviews of their data into easy to understand dashboards. Those applications are namely increasingly built into cloud, so the easiest implementation would be – you guessed it – if data warehouse is also in the cloud.

To ease the data operations, a proper data management will help you organize, integrate and manage access to data across the organisation, from IT, to sales, to executives. After all, you want to focus on deriving insight from data – not configuring, tuning, and managing a data warehouse.

  1. We are one of the most experienced and senior European Snowflake partners with a “Person of the year” award from Snowflake for Central and Eastern Europe. One of the leaders in data management, data integration and BI. We can help you easily bring together all your data and enable all your users to perform cutting-edge analytics.

There is no comparable tool in the marketplace that provides the benefits of a cloud with a simple learning curve and minimal administration. It allows organisations to move to cloud quickly and focus on business value.

From Walker Survey, May 2019