5 Advantages of Using a Redshift Data Warehouse

Choosing the right solution to warehouse your data is just as important as how you collect data for business intelligence….

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Choosing the right solution to warehouse your data is just as important as how you collect data for business intelligence. To extract the maximum value from your data, it needs to be accessible, well-sorted, and easy to manipulate and store. Amazon’s Redshift data warehouse tools offer such a blend of features, but even so, it’s important to understand what it brings to the table before making a decision to integrate the system.

So, what are the benefits of switching data storage to Redshift data warehouses? In addition to its significant storage capacity, the data warehousing solution delivers several key benefits that make it an intriguing and possibly ideal choice for business intelligence. These are five of the biggest advantages of using Redshift for your business intelligence needs.

It Offers Significant Query Speed Upgrades

With larger datasets—especially when reaching petabytes of magnitude—querying experiences an understandable lag in speed. However, most database and warehouse solutions today offer the ability to process requests and other functions in parallel. Redshift data warehouse architecture has clocked in at some of the fastest general and query speeds.

Comparing Redshift vs Hadoop, for instance, shows that overall the former is nearly 10 times faster than the latter. In some query tests, Redshift database easily outstrips Hadoop in returning results. Amazon’s Massively Parallel Processing lets BI tools with the Redshift connector process several queries across multiple nodes simultaneously while reducing workloads.


Redshift Database

It Focuses on Ease of Use and Accessibility

Even though it’s more than 30 years old, MySQL (and other SQL-based systems) remains one of the most popular and easily usable interfaces for database management. Its simple query-based system makes platform adoption and acclimation a breeze. Instead of building a completely new interface that requires significant resources and time to learn, Amazon chose to create a platform that works much like MySQL, to great effect.

While it does change some aspects, Redshift keeps much of what makes MySQL, including the back-end tools that work with PostgreSQL, JDBC, and ODBC drivers while making it easy to connect with most business intelligence tools. Moreover, it can easily connect with other existing tools and provides an easy learning curve for new administrators and even end-users.

It Provides Fast Scaling With Few Complications

Redshift is cloud-based and hosted directly on Amazon Web Services, the company’s existing cloud infrastructure. One of the biggest benefits this provides Redshift is a flexible architecture that can scale in seconds to meet changing storage demands. A major issue facing organizations with rapidly changing data requirements is that scaling can be both costly and complex.

Thanks to AWS, Redshift can be scaled up or down by quickly activating individual nodes of varying sizes. This scalability also means cost savings, as companies aren’t forced to spend money maintaining servers that are unused or to quickly purchase expensive server space when the need arises. This is especially useful for smaller companies which experience significant growth and must scale their existing solutions.

It Keeps Costs Relatively Low

Amazon Web Services bills itself as a cost-effective solution for companies of all sizes. In keeping with the company line, Redshift provides a similar pricing model that delivers greater flexibility while empowering companies to keep a tighter watch on their data warehousing costs. This pricing capability comes as a result of the company’s cloud infrastructure, and its ability to keep workloads to a minimum on most nodes.

Additionally, organizations can choose which type of pricing model they prefer: on-demand or reserved instances. The first is generally more appealing to smaller companies, or those with lighter data warehousing needs, while the latter offers a more stable ecosystem for data storage. More than simple dollars and cents, this pricing flexibility means you can always ensure that scalability is possible and straightforward.

It Gives You Robust Security Tools

Massive data sets often contain sensitive data, and even if they don’t, they still hold important information about their organizations. As such, the right data warehouse solution should have powerful protection tools to lock down data. Redshift presents a few different encryption and security tools that make protecting warehouses even easier.

This includes a VPC for network isolation as well as different access control tools that give you more granular management capabilities. Additionally, Redshift includes SSL encryption for data in transit, and AWS’ S3 servers offer both client- and server-side encryption, giving you greater control over when data is viewable and accessible.

Choosing the Right Warehouse

Building a successful BI ecosystem for your organization begins with data. By choosing a warehouse that meets your requirements and grants you the flexibility to grow and scale, you can give your business intelligence even greater value while concurrently deriving much better insights and analytics.


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