AWS Redshift is a popular data warehousing solution that can handle data on an exabytes scale. You may be considering the service for a number of use cases such as processing real-time analytics, combining multiple data sources, log analysis, or more.
Made possible by its Massively Parallel Processing (MPP) technology, Redshift is able to execute operations on a humongous volume of data at lightning speed — while typically costing only a fraction of what competitors like Oracle and Teradata charge for comparable products.
To cover the AWS data warehouse in more detail and help you decide if Redshift is the right solution for you, this article will answer:
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AWS Redshift is a data warehousing solution from Amazon Web Services. Redshift shines in its ability to handle huge volumes of data — capable of processing structured and unstructured data in the range of exabytes (1018 bytes). However, the service can also be used for large-scale data migrations.
Similar to many other AWS services, it can be deployed with just a few clicks and provides a plethora of options to import data. Additionally, the data in Redshift is always encrypted for added security.
Redshift helps to gather valuable insights from a large amount of data. With the easy-to-use interface of AWS, you can start a new cluster in a couple of minutes, and you don’t have to worry about managing infrastructure.
Redshift is an OLAP-style (Online Analytical Processing) column-oriented database. It is based on PostgreSQL version 8.0.2. This means regular SQL queries can be used with Redshift. But this is not what separates it from other services. The fast delivery to queries made on a large database with exabytes of data is what helps Redshift stand out.
Fast querying is made possible by Massively Parallel Processing design or MPP. The technology was developed by ParAccel. With MPP, a large number of computer processors work in parallel to deliver the required computations. Sometimes processors situated across multiple servers can be used to deliver a process.
Unlike most MPP vendors, ParAccel does not sell MPP devices. Their software can be used on any hardware to harness the power of multiple processors. AWS Redshift uses the MPP technology of ParAccel. In fact, Redshift was started following capital investment by AWS in ParAccel and using MPP technology from ParAccel. Now the company is part of Actian.
Amazon Redshift is used when the data to be analyzed is humongous. The data has to be at least of a petabyte-scale (1015 bytes) for Redshift to be a viable solution. The MPP technology used by Redshift can be leveraged only at that scale. Beyond the size of data, there are some specific use cases that warrant its use.
Many companies need to make decisions based on real-time data and often need to implement solutions quickly too. Take Uber for example.
Based on historical and current data, Uber has to make decisions quickly. It has to decide surge pricing, where to send drivers, what route to take, expected traffic, and a whole host of data.
Thousands of such decisions have to be made every minute for a company like Uber with operations across the globe. The current stream of data and historical data has to be processed in order to make those decisions and ensure smooth operations. Such instances can use Redshift as the MPP technology to make accessing and processing data faster.
There are occasions where structured data, semi-structured data, and/or unstructured data have to be processed to gain insights. Traditional business intelligence tools lack the capability to handle the varied structures of data from different sources. Amazon Redshift is a potent tool in such use cases.
The data of an organization needs to be handled by a lot of different people. All of them are not necessarily data scientists and will not be familiar with the programming tools used by engineers.
They can rely on detailed reports and information dashboards that have an easy-to-use interface. Highly functional dashboards and automatic report creation can be built using Redshift. It can be used with tools like Amazon Quicksight and also third-party tools created by AWS partners.
Behavior analytics is a powerful source for useful insights. Behavior analytics provide information on how a user uses an application, how they interact with it, the duration of use, their clicks, sensor data, and a plethora of other data.
The data can be collected from multiple sources — including a web application used on a desktop, mobile phone, or tablet — and can be aggregated and analyzed to gain insight into user behavior. This coalescing of complex datasets and computing data can be done using Redshift.
Redshift can also be used for traditional data warehousing. But solutions like the S3 data lake would likely be better suited for that. Redshift can be used to perform operations on data in S3, and save the output in S3 or Redshift.
The very distinctive advantage of using AWS Redshift is the cost-benefit to your organization. It costs only a fraction (roughly one-twentieth) of the cost of competitors like Teradata and Oracle.
In addition to cost, there are a number of benefits to using Redshift.
The data collected will grow every day. Redshift is a hedge against the growing data with increasing analytical complexity. It can be used to build infrastructure that lasts into the future.
Additionally, Redshift offers best in class performance at a fraction of the cost of competitors. This makes it a value proposition for any organization that has to handle large volumes of data.
Redshift has some drawbacks that need to be considered before choosing it as your data warehousing solution.
AWS offers a very flexible pricing scheme for Redshift. The price starts at $0.25 per hour for a terabyte of data and it can be scaled from there. First, you need to opt for the node type you want. AWS Redshift offers three types of nodes.
Prices at US-North California center
Redshift also has a pay-as-you-go pricing model according to the requirements.
Detailed pricing details are provided on the AWS Redshift pricing page.
AWS Redshift can integrate with Amazon S3, AWS Glue, Amazon Kinesis Data Firehose, Amazon Quicksight, and over 170 other AWS services. Though each of these services has its advantages, using all of them simultaneously can drastically inflate your AWS bill.
Many of the services you use might be redundant, and there will be better ways to reduce costs.
Additionally, mapping costs from specific services that make up your products and features can be a nearly impossible task when done manually or using a traditional cloud cost management tool.
Whether your goal is to reduce your AWS bill, understand your cloud costs, or map costs to the products or features your business cares about, CloudZero can help you achieve all three and gain true cloud cost visibility. Request a demo to see CloudZero in action and learn more about how it can help you optimize your Redshift and other AWS costs.