Databases: Managed vs Unmanaged, SQL vs NoSQL

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Questions and Answers

What is the primary difference between managed and unmanaged database solutions?

  • Unmanaged solutions handle scaling, fault tolerance, and availability automatically.
  • There is no difference; the terms are interchangeable.
  • Scaling, fault tolerance, and availability are typically built into managed solutions. (correct)
  • Managed solutions require more hands-on administration.

Which of the following is a major challenge associated with traditional relational databases that Amazon RDS aims to address?

  • Reduced data security concerns.
  • Limits on scalability and complex maintenance. (correct)
  • Automated application optimization.
  • Simplified data querying processes.

In the context of database services, what responsibilities are typically handled by the user when using Amazon RDS?

  • Database software installation and patching.
  • High availability configuration.
  • Operating system installation and patching.
  • Application optimization. (correct)

Which of the following databases is NOT supported as an engine within Amazon RDS?

<p>MongoDB (A)</p> Signup and view all the answers

What is a key difference between relational (SQL) and non-relational (NoSQL) databases regarding data storage?

<p>Relational databases use fixed schemas, while NoSQL databases often use dynamic schemas. (A)</p> Signup and view all the answers

Which of the following is a primary characteristic of Amazon DynamoDB?

<p>Virtually unlimited storage and scalable throughput. (D)</p> Signup and view all the answers

In Amazon DynamoDB, what are the two types of primary keys that can be defined when creating a table?

<p>Partition key and Sort key (A)</p> Signup and view all the answers

What is the core function of Amazon Redshift?

<p>Serving as a fast and cost-effective data warehouse. (B)</p> Signup and view all the answers

Which of the following best describes the architecture of Amazon Redshift?

<p>A distributed system consisting of clusters with leader and compute nodes. (D)</p> Signup and view all the answers

Which of the following is a typical use case for Amazon Redshift?

<p>Enterprise data warehousing (EDW). (C)</p> Signup and view all the answers

How does Amazon Redshift support SaaS providers in managing their data warehouse needs?

<p>By scaling data warehouse capacity as demand grows. (B)</p> Signup and view all the answers

What aspects of database management does Amazon Aurora automate to simplify database administration?

<p>Backup, recovery, failure detection, and repair. (C)</p> Signup and view all the answers

Which of the following is a key benefit of using Amazon Aurora?

<p>Fast performance, high availability, and managed service. (D)</p> Signup and view all the answers

What does it mean that Amazon Aurora is 'compatible'?

<p>It is compatible with MySQL and PostgreSQL. (A)</p> Signup and view all the answers

How does Amazon Aurora's 'pay-as-you-go' pricing model benefit users?

<p>Users pay based on consumption of resources, reducing upfront costs. (D)</p> Signup and view all the answers

Flashcards

Amazon RDS

A managed database service offering various database engines.

Amazon DynamoDB

A NoSQL database service with virtually unlimited storage.

Amazon Redshift

A fast, managed data warehouse service for cost-effective scaling.

Amazon Aurora

Compatibility with MySQL and PostgreSQL with automated management.

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Unmanaged Database

Scaling, fault tolerance, and availability are managed by the user.

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Managed Database

Scaling, fault tolerance, and availability are typically built into the service.

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Relational (SQL) Database

Data is stored in rows and columns with a fixed schema, queried using SQL.

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Non-Relational (NoSQL) Database

Data storage focuses on collections of documents with dynamic schemas.

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Partition Key

A primary key consisting of a single attribute.

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Partition and Sort Key

A primary key composed of partition key and sort key.

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Redshift Use Case: EDW

An Enterprise Data Warehouse (EDW) solution in the cloud.

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Redshift Use Case: Big Data

Analyzing large datasets for insights and trends.

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SaaS Data Warehousing

Scalable data warehouse capacity as demand grows.

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Study Notes

  • Module 8 covers Databases

Introduction

  • Managed databases have scaling, fault tolerance, and availability built-in.
  • Unmanaged databases require manual management of scaling, fault tolerance, and availability.
  • SQL databases are relational, while NoSQL databases are non-relational.
  • Choose a database service based on specific business requirements.

Challenges of Relational Databases

  • Relational databases can have slower maintenance and larger footprints.
  • Software installation and patching are required.
  • Database backups and ensuring high availability can be complex.
  • Scalability can be limited.
  • Data security concerns.
  • Operating system installation and patches needed.
  • Amazon RDS (Relational Database Service) handles OS installation and patches, database software installation and patches, database backups, high availability, and scaling; users manage application optimization.

Amazon RDS

  • Supports six database engines: MySQL, Amazon Aurora, Microsoft SQL Server, PostgreSQL, MariaDB, and Oracle.

Relational (SQL) vs. Non-Relational (NoSQL) Databases

  • Relational databases use rows of columns for data storage, while non-relational use key-value pairs, documents, or graphs.
  • Relational databases have fixed schemas, while non-relational have dynamic schemas.
  • SQL is used for querying relational databases.
  • Relational databases scale vertically, while non-relational scale horizontally.
  • Non-relational databases focus on collections of documents.

Amazon DynamoDB

  • A fast and flexible NoSQL database service.
  • Offers virtually unlimited storage.
  • Allows items to have differing attributes.
  • Provides low-latency performance.
  • Designed for scalable read/write throughput.
  • Core components: tables, items, and attributes.
  • Two kinds of primary keys: Partition key and Partition & sort key.

Amazon Redshift

  • A fast, scalable, and cost-effective data warehouse.
  • Simple to set up and use.
  • Consists of clusters of leader and compute nodes.
  • Automation includes managing & monitoring, and scaling.

Amazon Redshift Use Cases

  • Enterprise Data Warehouse (EDW).
  • Big Data analytics.
  • Software as a Service (SaaS) solutions.
  • Scale the data warehouse capacity as demand grows.
  • Add analytic functionality to applications.
  • Reduce hardware and software costs.
  • Experimentation without large upfront costs.
  • Faster response to business needs.
  • Low price point for small customers.
  • Managed service handles deployment and maintenance.

Amazon Aurora

  • Enterprise-class relational database.
  • Compatible with MySQL and PostgreSQL.
  • Automates time-consuming tasks like backup, recovery, failure detection, and repair.

Amazon Aurora Service Benefits

  • Fast and highly available.
  • Managed service.
  • Simple to use.
  • Compatible with existing systems.
  • Pay-as-you-go pricing.

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