Cloud Analysts prognosticate that by 2020, open-source Database Management System (DBMS) services will account for more than 20% of the revenue of cloud services. Despite the unexpected rise of unstructured analytics platforms such as Hadoop, relational technology will use for at least 70 percent of new applications and projects.
However, it seems that traditional in-house databases are on the wane. By 2023, the Cloud will house three-fourths of all the databases. It leads to a resurgence of the relatively mature database space driven by cloud DB sales. It has been driven by double-digit annual growth figures into a market of $40 billion a year.
One of the primary reasons for the rise in the DBaaS services is Data Warehouse.
It is estimated that migration to cloud-based data warehouse solutions today is around 10 times the number of on-site solutions adopted. Moreover, 29% of the 800 data engineers, scientists and analysts surveyed said that “they still use a data warehouse on-site”; while 23% said that they do not use any data warehouse solution at all; This is showing that the move to the Cloud is not yet complete; as per the reports of panoply.
While Amazon’s Redshift remains the data warehouse leader across all companies and industries, the report found that it has lost substantial market share to other offerings. In 2017, 60% of respondents were using RedShift, while only 40% reportedly using RedShift in 2018.
Other industry leaders such as BigQuery and Microsoft Azure SQL Data Warehouse are not picking the slack significantly, but young players like Snowflake and Oracle are emerging as new contenders.
What is Database as a Service (DBaaS)?
The Database as a Service model allows access to a database through Cloud. It does not require any physical hardware, installing software or configuring performance.
Informally, these services are collectively known as “cloud databases.” The reason is that a DBaaS vendor maintained the DB in the Cloud, and application owners are paying a fee for its use. Typically, these payments are by use, but pricing models vary from a flat fee to an hourly rate to IO and other services charges.
As you shop, be cautious that the cloud DBs can be either standard relational databases or non-relational databases. They make sense for those who do not have the staff, the in-house expertise, or the desire to implement, manage, and maintain an in-house database. Hence, the usage among SMBs is high. However, mid-size firms and even some of the large firms as well may be tempted to outsource the function, at least for some databases.
Another factor in adoption is business growth. Where growth rates are very high, and it is difficult to predict future growth, the cloud model can be used as a temporary measure while attracting in-house teams play catch up. Still more and more companies are comfortable having some DBs in the Cloud, while the jewels of the companies remain in an on-premise DB.
What is a Data Warehouse?
A data warehouse is a repository of data that can be analyzed to make well-informed decisions. Data flows from transactional systems, relational databases, and other sources into the data warehouse; should be on a regular cadence. Business analysts, data scientists, and decision-makers use business intelligence (BI) tools, SQL clients, and other analytics applications to access the data.
Businesses anticipate the market and stay ahead of their competitors with accurate analytics, reports, and monitoring to make critical decisions. These reports, dashboards, and analytics tools are powered by data warehouses that efficiently store data to minimize I/O and concurrently deliver query results at blazing speeds. To hundreds and thousands of users.
Purpose of Data Warehouse
There are technologies to support decision making that help to use the available data in a data warehouse. These technologies help CXOs to use the warehouse quickly and effectively. They can accumulate data, analyze it, and make decisions based on the warehouse information. You can use the gathered information of the warehouse in any form, here are a few use cases.
Harmonizing Production Strategies: By collecting and comparing the previous year, data product strategies can be well-tuned by repositioning the products and managing the product portfolios.
Persona study: Customer persona can be created by analyzing the market need, buying preference and budget cycles, etc.
Operations Analysis: In the management of customer relationships and making environmental corrections, data warehousing also helps. The information also enables you to analyze business operations.
Cloud Data Warehouse
The emergence of the cloud data warehouse is becoming the most significant change in the data warehousing in recent times. Previously, installing a data warehouse required a considerable amount of investment in IT resources. Now, cloud computing vendor offers data warehouse as a service that you set up in minutes and start using it; you can access it via internet connection. This model negates the expensive capital and management expenditure required for a data warehouse on-site.
The Architecture of Cloud Data Warehouse
Each cloud service provider has its unique architecture for the cloud data warehouse; however, there some common architectural trends that you should beforehand while selecting a cloud vendor.
Massively Parallel Processing: Many leading cloud data warehouse vendors use massively parallel processing architecture, in this data get divided across many servers or nodes, with its processor. This MPP design provides much faster data querying since it coordinates query workloads over processors simultaneously.
Columnar storage: In a columnar database, tables are stored based on column values instead of row values. This design reduces the time needed to answer requests to lead to greater performance.
Serverless: This concept is developed by leading cloud service providers. In this architecture type, you don’t need to provision or manage any infrastructure.
Security and Compliance requirement
Security and compliance are the primary concern for enterprises considering a cloud data warehouse service, and rightly so. It’s no surprise that decision-makers are concerned about the risks of information security breaches in the Cloud — when data is trusted in the hands of the vendor, this can cause fear due to a lack of control. The fear of security issues is further rising when you consider the data warehouse to be a core component of business intelligence.
Due diligence is imperative and ensuring that potential cloud vendors in the data warehouse can meet all of your security and data protection requirements. Important things to look out for:
1. Strong user authentication policies
2. Data encryption
3. Compliance with essential industry regulations, for example, HIPAA for protected health information
4. Neatly done documentation highlights the vendor’s policies for data security, protection, archiving, and replication on virtualized environments and the underlying hardware
Today, organizations are fully embracing the cloud data warehousing; however, recognizing that what a cloud data warehouse needs to do has evolved with changes in cloud computing, automation, machine learning, big data, and other significant trends. A CDW is no going to end soon in itself; but rather as a stage in the data-driven journey, involving, among other considerations,
• The management of a data lifecycle,
• Ensuring data quality,
• Providing a data governance framework.
Once you have decided to hold the transition; ensure that your company builds a strong relationship with your chosen vendor, and focusing on responsiveness, performance, and functionality.