Snowflake - a cloud data platform for data-driven business needs

Snowflake – a cloud data platform for data-driven business needs

According to forecasts, the global big data and business analytics market will grow up to 274.3 billion US-Dollar by 2022 (from 189.1 billion US-Dollar in 2019; source: cognetik.com). This means that more and more businesses will invest in data analytics.

Cloud-based services will be a key to manage not only the massive amounts of data but also the necessary processing power. Service providers who cater to the individual needs of companies when it comes to data storage and processing, will become crucial for the further development of big data and business analytics.

Snowflake, a Californian company that raised more than 1.4 billion US-Dollars in development capital between 2012 to 2020 before going public, offers Relational Database Management Systems (RDBMS) that can be easily scaled. It serves a wide range of technology areas including data integration, business intelligence, advanced analytics, security and governance and supports most programming languages.

What is a Relational Database Management System?

A relational database uses a structure that allows to identify and access data in relation to other data sets in the database. A Relational Database Management System helps create, update and administer the relational database.

Snowflake offers a unique and real alternative to traditional RDBMS systems because it combines massive data storage with the ability to launch multiple data analytics processes in real time. Thanks to its technology, multiple processes can be executed in parallel by the same customer without competing with each other. Unlike traditional databases, these workloads are not executed on the data server, so they perform much better.

An architecture capable of handling and replicating billions of records anywhere

Snowflake’s architecture is based on a software infrastructure designed to manage semi-structured data, in XML or JSON format, which can handle billions of data, combined with a query mode that remains based on SQL. Since it makes use of the Cloud, users benefit from elastic computing resources that adapt to storage and computing needs. In 96% of cases, Snowflake is therefore capable of providing a new independent pool of resources in less than a second.

Data is stored by clients on a single regional instance, but a data sharing feature allows data to be replicated in other regions, independent of cloud, AWS, Azure or, more recently, Google Cloud Platform. These replications will be refreshed to reflect changes in the main database. To further facilitate data sharing, Snowflake has launched a data storage feature called “Data Market Place”. This allows data sets to be marketed and distributed internally or to partners via private spaces.

Snowflake’s pricing model: pay what you use

Snowflake is marketed as a managed and on-demand service. The pricing model includes only two elements: the cost of storage and the cost of computing resources consumed. The cost of storage is calculated per terabyte, compressed per month. The cost of computing is based on the processing units (credits) consumed to execute a request or provide a service. Calculation costs are charged based on actual usage, per second.

Snowflake announces new features

Currently, Snowflake is investing heavily in artificial intelligence and machine learning. Numerous connectors such as Spark, Python and Apache Arrow are already available as well as optimized integrations with AutoML tools such as DataRobot, Dataiku, H20.ai and Amazon Sagemaker.

Additionally, Snowflake announced the following features:

Snowpark – A new developer experience that will allow data engineers, data scientists, and developers to write code in their languages of choice, using familiar programming concepts, execute workloads such as ETL/ELT, data preparation, and feature engineering on Snowflake.

Snowflake Data Marketplace – Enables any Snowflake customer to discover and access live, ready-to-query, third-party data sets from more than 100 data providers, without needing to copy files or move the data.

Unstructured Data – Support for unstructured data such as audio, video, pdfs, imaging data and more which will provide the ability to orchestrate pipeline executions of that data.

Row Access Policies – Customers will be able to advance their data governance across all data objects and workloads in Snowflake.

ec4u offers Snowflake services

As a consulting company that helps customers with their digital transformation, ec4u offers services for companies to design, develop and deploy end-to-end data and analytics solutions using Snowflake technologies. The consultants at ec4u have developed a wide range of services to make it easier for customers to modernize their data architecture with a cloud-based solution and/or leverage their data to accelerate their business. The services assist with the assessment, architecture, analysis and technical migration.