If you want to know about What is AWS Redshift, and how AWS users use it, read this AWS Redshift tutorial. It explains everything about this Amazon data warehouse product!
To help you out, we’ll shed some light on Amazon Redshift, including:
- What Is AWS Redshift?
- What Is AWS Redshift Used For?
- What Is AWS Redshift Based On?
- History of Amazon Redshift
- PADB for Amazon Redshift
- What Does AWS Redshift Do?
- What Is Amazon Redshift Service?
- What Is AWS Redshift Spectrum?
- What Is AWS Redshift and How Is It Different from RDS?
- What Is Amazon Redshift ODBC Driver?
- What Is AWS Redshift Cluster?
- What Is AWS-Lambda-Redshift-Loader?
- What Is AWS Redshift and Glue?
What Is AWS Redshift?
AWS Redshift is a data storage solution provided by Amazon. It can handle extensive data and proves reliable in terms of real-time analytics.
You can also use AWS Redshift to log analysis and combine various data sources.
This Amazon service is only possible due to Massively Parallel Processing (MPP).
No matter the size of your digital data, Redshift can execute operations on it at lightning speed. Another fantastic thing about AWS Redshift is its affordability in the market.
Also read- AWS Redshift Vs Snowflake: Which Data Warehouse To Choose
What Is AWS Redshift Used For?
Amazon Web Services brings AWS Redshift to the users for their data storage problems.
It is a data warehousing solution that can process a huge volume of structured or unstructured data. This data can be in exabytes (x1018 bytes)!
The processing of data is not the only use of AWS Redshift. It can also perform data migrations on a large scale.
The ability to handle data tremendously has given AWS Redshift the power to provide valuable insights.
Moreover, it works at an incredible speed by creating a new cluster within a few minutes. That alone is the reason for companies to use Redshift!
What Is AWS Redshift Based On?
AWS Redshift is based on PADB, which is based on PostgreSQL. So, it’s safe to say that Redshift is based on PostgreSQL, but not entirely, as it has its own uniqueness.
However, if you are familiar with PostgreSQL, you will be able to learn the Redshift features quickly.
History of Amazon Redshift
Like the other AWS services, Amazon Redshift is also not that old. It was introduced in 2012 as the first cloud-based data warehouse for AWS users. However, it is not a native Amazon product.
ParAccel is the company that built Redshift, and Amazon spent $20 million to get it from them. They spent the money on the licensure of using the ParAccel Analytic Database (PADB) code.
PADB for Amazon Redshift
PADB was unique among its competitors for its columnar database. It used commodity hardware so using it for cloud-based data storage was ideal.
ParAccel made quite a fortune from the Amazon deal, but Redshift proved more valuable and profitable for Amazon!
What Does AWS Redshift Do?
Following are some of the features that determine the working of AWS Redshift:
- AWS Redshift uses Online Transaction Processing (OLTP).
- It allows the organization of data into columns and rows based on the nature of the workload.
- Row-oriented systems are famous for their efficiency with small operations.
- Column-oriented systems are popular for their speed in accessing large datasets.
- It works on Massively Parallel Processing (MPP).
- The divide and conquer strategy is applied to large datasets.
- Massive processing task is broken down into smaller tasks.
- The small jobs are distributed to different processors for simultaneous computations.
- The divide-and-conquer method saves time.
- It offers end-to-end encryption of data.
- Redshift has customizable encryption options.
- Users can configure encryption based on their needs.
- They can use one of the two methods: customer-managed key or AWS-managed key.
- They can choose between Hardware Security Module (HSM) or AWS Key Management Service.
What Is Amazon Redshift Service?
Amazon Redshift service uses a data warehousing solution to improve the processing of large datasets. The service works on MPP, so there are no delays due to the high volume of data.
Using MPP technology, the service offers speed by breaking large processing jobs into smaller tasks. It delivers output quickly and remains unmatched in cloud-based data storage.
Users have the power to encrypt any Redshift operation and protect their data from potential harm. There is also the familiarity factor with similar features as PostgreSQL, so the service can work well with SQL queries.
What Is AWS Redshift Spectrum?
Amazon Redshift has various features, and one of the most popular is Redshift Spectrum. Here are the characteristics of AWS Redshift Spectrum:
- It offers a complex, efficient, and fast analysis of cloud-stored objects.
- The analysis is seamless given its embedded in the Amazon framework.
- It can process data inside an S3 bucket.
- As a result, it saves effort and time by analyzing the given data.
What Is AWS Redshift and How Is It Different from RDS?
AWS Redshift differs from RDS based on the following features:
|Redshift works best with millions of rows of queries, thanks to the sophisticated query optimizer.||RDS performs better with queries that do not test its limits. It’s perfect for queries that require low data scans.|
|Redshift requires administrative tasks to be conducted manually.||RDS has a simple architecture, so it requires low maintenance. Most administrative tasks are automated.|
|Redshift requires the user to manage the unique constraints in insertion keys.||RDS is rational data storage that thrives on row-oriented systems. It also supports unique key constraints.|
What Is Amazon Redshift ODBC Driver?
ODBC is a powerful Amazon Redshift driver that helps you connect with Redshift data in real-time.
If you have an application that supports ODBC, you can directly access the data from that application. Following features make the ODBC driver so unique and crucial for Amazon Redshift:
- Based on PostgreSQL and custom-made to connect with Amazon Redshift.
- Enables real-time data access.
- Provides SQL-92 capabilities for NoSQL data of Redshift.
- Allows flexible querying and automatic schema generation.
What Is AWS Redshift Cluster?
Amazon Redshift data warehouse has computing resources. They are called nodes. When these nodes are organized in a group, we call it an AWS Redshift cluster. Each cluster is unique in Redshift and has one or more databases. It also runs the Redshift engine.
- Each cluster has a Leader node and Compute nodes. The leader node is always only one, but Compute nodes can be more than one.
- The Leader node has the task of getting in touch with client applications.
- It receives queries and parses them to develop query execution plans.
- It coordinates with the compute nodes for the parallel execution of those queries.
- It returns the aggregated results to the applications.
What Is AWS-Lambda-Redshift-Loader?
AWS Lambda Redshift Loader is the function of sending data from AWS Lambda to Redshift. Suppose you have the AWS Lambda Amazon Redshift Database Loader along with the Active Amazon Redshift Cluster. In that case, you can follow these steps to move data:
- Download the AWS Lambda Amazon Redshift Database Loader.
- Make configurations to the Redshift Cluster and allow access from external sources.
- Enable the Lambda Function.
- Configure an event source to take requests from the S3 buckets for Amazon Lambda.
What Is AWS Redshift and Glue?
AWS Glue and Amazon Redshift work in unison when needed to move data.
When data is taken into or out of an Amazon Redshift cluster, AWS Glue helps Redshift by issuing COPY and UNLOAD statements. This results in maximum throughput.
AWS Glue uses temporary credentials to work with the Redshift cluster, but the credentials expire within an hour, which becomes problematic when working on long-running tasks.
What Is Amazon Redshift Serverless?
Although Amazon Redshift is a real-time data warehousing service, it also comes with a serverless option.
Amazon Redshift Serverless makes the analysis of data easier by eliminating the need to spend time setting up a data warehouse and managing it.
The Redshift Serverless enables users to get helpful insight by uploading and querying data.
The performance of a Serverless data warehouse is fast and efficient, with the option to scale in seconds automatically. It also saves costs for users!
Let us see what the Redshift Architecture looks like.
What Is Amazon Redshift vs S3?
AWS Redshift and Simple Storage Service (S3) are often confused as one service. Most newcomers are unaware of the distinct difference between these Amazon services, but you can understand it with this:
|Amazon Redshift||Amazon S3|
|Redshift is a data warehouse service.||S3 is an object storage service.|
|It deals with structured data that is ingested into the warehouse.||It can work with any size or structure of data. There is no need for predefined details.|
|It is perfect for BI tools and SQL-based clients.||It is ideal for data exploration and discovery.|
AWS redshift pricing
The smallest instance of Redshift Managed Storage starts from $.25 per hour. And of course, the prices go up depending on the storage and processing.
But for larger nodes, the prices can go up to $6 per hour.
It also depends on the type of node you are choosing like Dense Compute or an RA3 node.
Redshift Serverless is anyways priced in a different format. You get an hour of computing free. After that, it’s $0.50 per hour.
Additional billing for data transfer both incoming and outgoing of Redshift. You have to shell out extra bucks for additional features like scaling concurrency, backup, spectrum, and ML features.
AWS redshift Features
So, what are the features of Redshift that makes it the most liked DB for large data storage system? Let us find out
- Fault Tolerant – Redshift which operates with multiple nodes and saves multiple copies of data can handle node failures.
- Columnar Storage – Redshift is a columnar storage DB that can be arranged based on the workload making it fast.
- Data Compression – Data in Redshift can be compressed and each column of data can be compressed in different formats depending on the type of data.
- MPP – Redshift is a massively Parallel Processing DB, with multiple worker nodes it can distribute the processing across different nodes for faster processing.
- Concurrency Limit – Users can provision nodes based on the power of processing they want and can concurrently process data.
- Encrypted – The data in Redshift can be encrypted as per standards either with AWS-managed keys or customer-managed keys making it secure.
AWS Redshift vs Athena
This is an interesting topic, let us see how they are different.
|This is an MPP, columnar storage database||This is not a database but just a platform to query data|
|Can query data stored in the Database for analytical purpose||Can query data stored in the Database for analytical purposes|
|Supports complex queries, joins and pretty fast||Doesn’t supports complex queries, or joins. Use to run basic queries on S3 data|
|Requires the Redshift cluster to be set up initially, data loaded in it||Requires no setup, jut write and run the query on S3 bucket data.|
|This DB does not hold the Primary key constraint. We can have duplicate data in the table.||As the data is queried from Athena so we can have any type of data in the S3 bucket, duplicates as well.|
|Can query data from all kinds of files in an S3 bucket like JSON, CSV, PARQUE, AVRO, TSV, and ORC.||Can query data from all kinds of files in an S3 bucket like JSON, CSV, PARQUE, AVRO, TSV and ORC.|
Amazon Redshift increases the efficiency of data analytics and provides insight in a short amount of time.
That’s why many users prefer this service to save time and effort! There is no limitation for data size as it can deliver performance-based results regardless of the number of rows of data.
The parallel processing technology and faster output make real-time analysis easier for customers.
If you have been wondering about Amazon Redshift data warehouse service and why you should use it, we hope this article has helped you!
It has a complete AWS redshift developer guide explanation.
FAQs: What Is AWS Redshift
Q: Is Redshift a SQL Database?
Amazon Redshift is based on industry-level SQL, but it’s a lot more than that.
The added features allow the management of large datasets and enable analytics with high performance.
Q: What Is the Purpose of Amazon Redshift?
Amazon Redshift provides a data warehousing solution for users who are looking for cloud-based data storage.
It is a fully-managed service with a scalability feature that enables users to go from gigabytes of data to petabytes!
Q: What Is Redshift, and How Does It Work?
Redshift has a Leader node, and one or more Compute nodes that work by dividing large data jobs into smaller, manageable jobs.
Each node works on the part of disk space and memory.
The Leader node distributes the data to the compute nodes and manages the query operations until it sends the results to the client application.
I am an Amazon Web Services Professional, having more than 11 years of experience in AWS and other technologies. Extensively working in various AWS tools like S3, Lambda, API, Kinesis, Load Balancers, EKS, ECS, and many more. Working as a Solution Architect and Technology Lead for Architecting and implementing the same for different clients. He provides expert solutions around the world and especially in countries like the United States, Canada, United Kingdom, Australia, New Zealand, etc. Check out the complete profile on About us.