AWS DynamoDB

 DynamoDB allows users to create databases capable of storing and retrieving any amount of data and comes in handy while serving any amount of traffic. It dynamically manages each customer’s requests and provides high performance by automatically distributing data and traffic over servers. It is a fully managed NoSQL database service that is fast, predictable in terms of performance, and seamlessly scalable. It relieves the user from the administrative burdens of operating and scaling a distributed database as the user doesn’t have to worry about hardware provisioning, patching Softwares, or cluster scaling. It also eliminates the operational burden and complexity involved in protecting sensitive data by providing encryption at REST. 

DynamoDB Vs RDBMS

The below table provides us with core differences between a conventional relational database management system and AWS DynamoDB: 

OperationsDynamoDBRDBMS
Source connectionIt uses HTTP requests and API operations.It uses a persistent connection and SQL commands.
Create TableIt mainly requires the Primary key and no schema on the creation and can have various data sources.It requires a well-defined table for its operations.
Getting Table InformationOnly Primary keys are revealed.All data inside the table is accessible.
Loading Table DataIn tables, it uses items made of attributes.It uses rows made of columns.
Reading Table DataIt uses GetItem, Query, and ScanIt uses SELECT statements and filtering statements.
Managing IndexesIt uses a secondary index to achieve the same function. It requires specifications (partition key and sort key).Standard Indexes created by SQL is used.
Modifying Table DataIt uses a UpdateItem operation.It uses an UPDATE statement.
Deleting Table DataIt uses a DeleteItem operation.It uses a DELETE statement.
Deleting TableIt uses a DeleteTable operation.It uses a DROP TABLE statement.

Advantage of DynamoDB:

The main advantages of opting for Dynamodb are listed below: 

  • It has fast and predictable performance.
  • It is highly scalable.
  • It offloads the administrative burden operation and scaling.
  • It offers encryption at REST for data protection.
  • Its scalability is highly flexible.
  • AWS Management Console can be used to monitor resource utilization and performance metrics.
  • It provides on-demand backups.
  • It enables point-in-time recovery for your Amazon DynamoDB tables. Point-in-time recovery helps protect your tables from accidental write or delete operations. With point-in-time recovery, you can restore that table to any point in time during the last 35 days.
  • It can be highly automated. 
     

Limitations of DynamoDB –

The below list provides us with the limitations of Amazon DynamoDB: 

  • It has a low read capacity unit of 4kB per second and a write capacity unit of 1KB per second.
  • All tables and global secondary indexes must have a minimum of one read and one write capacity unit.
  • Table sizes have no limits, but accounts have a 256 table limit unless you request a higher cap.
  • Only Five local and twenty global secondary (default quota) indexes per table are permitted.
  • DynamoDB does not prevent the use of reserved words as names.
  • Partition key length and value minimum length sits at 1 byte, and maximum at 2048 bytes, however, DynamoDB places no limit on values.

Comments

Post a Comment

Popular posts from this blog

Terraform

Image
  Terraform is an infrastructure as code tool that lets you build, change, and version cloud and on-prem resources safely and efficiently. HashiCorp Terraform is an infrastructure as code tool that lets you define both cloud and on-prem resources in human-readable configuration files that you can version, reuse, and share. You can then use a consistent workflow to provision and manage all of your infrastructure throughout its lifecycle. Terraform can manage low-level components like compute, storage, and networking resources, as well as high-level components like DNS entries and SaaS features. How does Terraform work? Terraform creates and manages resources on cloud platforms and other services through their application programming interfaces (APIs). Providers enable Terraform to work with virtually any platform or service with an accessible API. HashiCorp and the Terraform community have already written  thousands of providers  to manage many different types of resources and services.
Read more

Scrum Master Interview help - Bootcamp

Understanding the MoSCoW prioritization | How to implement it into your project Projects, irrespective of their size or complexity, often juggle numerous tasks and requirements. In such a scenario,  MoSCoW prioritization  becomes essential to ensure the successful completion of the project.  Besides, it is also a very effective way to manage project priorities. With a straightforward and adaptable approach, the MoSCoW method helps manage stakeholder expectations and improve project outcomes. What is the MoSCoW prioritization technique?  The MoSCoW method is a prioritization matrix widely used in project management and software development. The term MoSCoW is an acronym that stands for  Must have ,  Should have ,  Could have , and  Won’t have , each denoting a level of priority. Here is the breakdown of the MoSCoW method:  Must have:  These are critical requirements that the project cannot be completed without them. If these are not fulfilled, the project is con
Read more

Kubernetes

  Using containers to host applications and other processes has gone mainstream. As more and more workload is moved into containers, management systems are needed to handle the demands of containerized applications at scale. One of the most popular options for managing  container-based workload is Kubernetes . Kubernetes combines container management automation with an extensible API to create a cloud-native application management powerhouse. At its core, Kubernetes manages the placement of pods, which can consist of one or more containers, on a Kubernetes cluster node. Additionally, if one of these pods crashes, Kubernetes can create a new instance of it. If a cluster node is removed, Kubernetes can move any affected workload to a different node in the cluster. On top of that, Kubernetes pods can be scaled to provide more or less throughput to meet scale demands and these scale operations can be triggered manually or automatically using Kuberentes horizontal pod auto-scaling. Finally,
Read more