Amazon Redshift is one of the most widely used cloud data warehouses and analytics services among enterprises today — chiefly for its ease of use and capacity to handle exabytes of data at lightning speeds, and for being far more cost-effective than other data warehouse solutions. Run by Amazon Web Services (AWS), Amazon Redshift is used for multiple business use cases such as powering business intelligence tools, operational analytics, and user behavior analytics. If you’re considering Amazon Redshift to optimize data analytics, here is a brief overview.
What is Amazon Redshift?
Amazon Redshift enables you to query and combine petabyte scale of structured and semi-structured data across your operational database, data warehouse, and data lake using standard SQL. You can save query results back to an S3 data lake using open formats, such as Apache Parquet or Optimized Row Columnar (ORC), which enables you to perform additional analytic queries. It uses Massively Parallel Processing (MPP) technology and, like most AWS services, is easy to deploy with just a few clicks, with many options to import data. There are also numerous tutorials to help you quickly understand how to get a Redshift cluster up and running in minutes. It delivers high performance and fast performance — imperative to enterprises today.
It’s also known for its favorable pricing. AWS states that Amazon Redshift has up to 3X better price-performance than other cloud data warehouses and that the price-performance advantage improves as you expand from gigabytes to petabytes. How does it do this? By taking advantage of proprietary hardware and machine learning (ML), the Redshift database uses the AWS Nitro System to accelerate data compression and encryption, analyze queries, and graph optimization algorithms to automatically organize and store data for exceptionally fast results.
Additionally, Amazon offers AQUA (Advanced Query Accelerator) which is distributed and hardware accelerated cache that allows Redshift data queries to run up to 10X faster than other enterprise cloud data warehouses. It accelerates scanning, filtering, and aggregation operations, and Amazon reports it will accelerate more operations in the future.
Overall, Amazon Redshift is easy to use, handles the massive amounts of big data that enterprises generate and consume, and alleviates the need to manage infrastructure.
What can I use Amazon Redshift for?
There are multiple business use cases for Amazon Redshift, including:
Business intelligence
Today’s enterprises run on the value of their data and require real-time data analytics to make fast, accurate business decisions. But not everyone is a data scientist. Redshift makes it easy for anyone who needs business intelligence to automatically configure and generate reports and dashboards, and integrate with tools such as Amazon Quicksight or other BI tools.
Operational analytics
In addition to BI, operations needs analytics on applications and systems. Redshift lets you bring together structured data from your data warehouse and semi-structure data such as application logs from your S3 data lake for real-time operational analytics.
Behavior analytics
Behavior analytics tells you how people use an application, such as how they interact with it, the duration of use, clicks, sensor data, and more. This data resides on web applications on desktops, mobiles, tablets and when aggregated is useful for determining how users (customers) behave. Redshift enables you to combine complex datasets to surface critical insights for product development and innovation.
What are the benefits of using Amazon Redshift?
While data volume, cost, and speed are major benefits, there are others, including:
- Security. Amazon handles the security of the cloud, while users are responsible for the security of applications in the cloud. Amazon provides access control, data encryption, and virtual private cloud to help you secure your data. It also has automatic back ups across different locations.
- Automation. You can automate tasks with Redshift, including scheduled reports, auditing, and maintenance.
- Scalability. Redshift scales automatically to support workload concurrency. This ensures that you have the capacity you need as you need it, without having to manually scale.
- Integration. Obviously, Amazon Redshift plays nice with other Amazon services, but the Redshift API also enables you to easily integrate Redshift into third-party apps and tools. Using an integration platform as a service (iPaaS), like SnapLogic, you can automate the integration process, easily create data pipelines, and make it easy for anyone in the enterprise to integrate data where needed.
- Partner Ecosystem. AWS has a strong partner ecosystem which provides a plethora of third-party applications and implementation services to choose from.
What is the Amazon Redshift pricing model?
One of the major benefits of Redshift is its flexible pricing model. They state that they cost less to operate than any other data warehouse, starting at $0.25 (2021 pricing) per hour and scaling up to petabytes of data and thousands of users. They offer pay-as-you-go pricing, on-demand pricing, as well as other models to help you ensure you buy what you need and can manage costs effectively. Additionally, they offer an AWS Redshift Pricing Calculator to help you navigate your options as well as guides to Amazon pricing.
Can I integrate Amazon Redshift with Snaplogic?
As mentioned earlier, you’ll need to integrate your data sources in a way that automates the process in real time. SnapLogic enables you to easily integrate data with multiple pre-built connectors without needing data scientists to do so. Snaplogic integrates with the Redshift API so you can be confident your data warehousing processes are automated and fast.
SnapLogic and Amazon Redshift have joined forces to simplify data integration and data warehousing via the cloud. Together, SnapLogic and AWS enable organizations to unlock critical insights and operational efficiencies through the democratization of data, increasing your organization’s ability to scale, respond, and compete effectively. With SnapLogic and AWS, data flows securely, without friction or impediment, across an entire organization, regardless of the source or application, bringing the best of the cloud to Amazon customers.
SnapLogic is a certified partner for native integration with the Amazon Redshift Console. Using SnapLogic, you can accelerate data onboarding and produce valuable insights in minutes, and quickly move data from hundreds of applications including Salesforce, Workday, ServiceNow, Google Analytics, Facebook Ads, Slack, Jira, Splunk, and Marketo into an Amazon Redshift data warehouse, in an efficient and streamlined way.
Learn more about how SnapLogic and Amazon Redshift work together.
Trivia Question: How did Amazon Redshift get its name?
No doubt you’ve googled “redshift” and come across a lot of talk about space, and expanding universes, and NASA (we did!). So, what is a “redshift” exactly? Well, in physics, a redshift is an increase in the wavelength and corresponding decrease in the frequency and photon energy of electromagnetic radiation, such as light. (By the way, the opposite is called a blueshift.) In astronomy, there are three main causes for a redshift:
- Radiation is traveling between distant objects that are moving apart (a relativistic redshift, like a relativistic doppler effect).
- Radiation is traveling towards an object in a weaker gravitational potential – a gravitational redshift.
- Radiation is traveling through an expanding space, like the expansion of the universe – a cosmological redshift. Incidentally, Hubble’s Law (after Edwin Hubble) is the observation that all sufficiently distant light sources show redshift corresponding to their distance from the Earth.
Why did AWS name it Redshift? Well, according to Google, it had nothing to do with physics and everything to do with moving away from their competitor Oracle’s corporate red branding — quite literally a shift away from Oracle’s red, aka “Redshift”. Clever, huh?
