What is Amazon Redshift?
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Amazon Redshift is a cloud data warehouse product built on top of ParAccel technology that handles large datasets and database migrations at petabyte scale. It differs from Amazon RDS in its ability to handle analytics workloads on big data using a columnar database. Redshift allows up to 16 petabytes of data storage compared to RDS Aurora's 128 terabytes. It uses parallel processing and compression to perform operations on billions of rows at once, making it useful for storing and analyzing large data volumes.
What is Amazon Redshift?
- 2. Amazon Redshift is a data warehouse product which forms part of the larger cloud-computing platform Amazon Web Services. It is built on top of technology from the massive parallel processing (MPP) data warehouse company ParAccel (later acquired by Actian), to handle large scale data sets and database migrations.Redshift differs from Amazon's other hosted database offering, Amazon RDS, in its ability to handle analytic workloads on big data data sets stored by a column-oriented DBMS principle. Redshift allows up to 16 petabytes of data on a cluster compared to Amazon RDS Aurora's maximum size of 128 terabytes. Amazon Redshift is based on an older version of PostgreSQL 8.0.2, and Redshift has made changes to that version. An initial preview beta was released in November 2012 and a full release was made available on February 15, 2013. The service can handle connections from most other applications using ODBC and JDBC connections. According to Cloud Data Warehouse report published by Forrester in Q4 2018, Amazon Redshift has the largest number of Cloud data warehouse deployments, with more than 6,500 deployments.
- 3. Redshift uses parallel-processing and compression to decrease command execution time. This allows Redshift to perform operations on billions of rows at once. This also makes Redshift useful for storing and analyzing large quantities of data from logs or live feeds through a source such as Amazon Kinesis Data Firehose. Tens of thousands of customers today rely on Amazon Redshift to analyze exabytes of data and run complex analytical queries, making it a widely used cloud data warehouse. Run and scale analytics in seconds on all your data without having to manage your data warehouse infrastructure.
- 4. Why we need Redshift? Amazon Redshift seemed like a solution for our problems of disk space and performance. It is a columnar database which is a fully managed, scalable, fast, and cost-effective data warehouse solution. Amazon Redshift’s columnar data storage, massively parallel processing (MPP) and efficient integration with other AWS services provided a very reliable and effective solution to business intelligence and analytics platform.
- 5. Use Case for Redshift Improve financial and demand forecasts Automatically create, train, and deploy machine learning models for predictive insights. Collaborate and share data Securely share data among accounts, organizations, and partners while building applications on top of third-party data.
- 6. Use Case for Redshift Optimize your business intelligence Build insight-driven reports and dashboards using Amazon QuickSight, Tableau, Microsoft PowerBI, or other business intelligence tools. Increase developer productivity Get simplified data access, ingest, and egress from numerous programming languages and platforms without configuring drivers and managing database connections.
- 7. Amazon Redshift uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and machine learning to deliver the best price performance at any scale.
- 8. Did you know that you can get Amazon Redshift for free? If you are new to Redshift (i.e. you’ve never created an Amazon Redshift cluster) you’re eligible for a two-month free trial. What is included? •A dc1.large server with 2 CPU, 15 GB Ram, and 160 GB SSD storage •Amazon will give you 750 hours each month, for two months This is a perfect solution to experiment with new analytic tools, kickstart a project or a proof-of-concept initiative. It is also a great way for you to get an enterprise-class data warehouse with little investment.
- 9. Benefits of Redshift •Optimized for Data Warehousing: Amazon Redshift has a massively parallel processing (MPP) data warehouse architecture, parallelizing and distributing SQL operations to take advantage of all available resources. •Encryption: With just a couple of parameter settings, you can set up Amazon Redshift to use SSL to secure data in transit and hardware- accelerated AES-256 encryption for data at rest. •Petabyte Scale: With a few clicks in console or a simple API call, you can easily change the number or type of nodes in your data warehouse and scale up all the way to a petabyte or more of compressed user data.
- 10. Benefits of Redshift •Query your Amazon S3 “data lake”: Redshift Spectrum enables you to run queries against exabytes of unstructured data in Amazon S3, with no loading or ETL required. •Fault Tolerant: Amazon Redshift has multiple features that enhance the reliability of your data warehouse cluster. •Automated Backups: Amazon Redshift automatically and continuously backs up new data to Amazon S3.
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