DynamoDB is also accessible via an HTTP API and also performs authentication & authorization via IAM roles, that makes it perfect for building serverless applications. If you're generating the recommendations and serving them to the user, DynamoDB's simple key-value access patterns make it a fast, reliable choice plus thats a very easy process. DynamoDB charges for reading, writing, and storing data in your DynamoDB tables, along with any optional features you choose to enable. DynamoDB has two capacity modes and those come with specific billing options for processing reads and writes on your tables: on-demand and provisioned. Our study concluded that Amazon DynamoDB required constant monitoring to adjust throughput to handle the pressure of the high volume, while Azure seamlessly accepted the excess data without flaw. They both had their pros and cons, but in the end, Azure was the clear winner.

1. Dynamodb Consistent Write
2. Dynamodb Consistency Option
3. Dynamodb Consistency
4. Dynamodb Console
5. Dynamodb Consistency Model

The pros and cons of a database engine for your business will likely depend upon your dev team and the applications you use. But, if you’re already using the AWS stack and need a NoSQL database, then you should first review what DynamoDB has to offer and how well it works for your use case. The biggest question is whether you want to set up. Amazon DynamoDB 's FeaturesAutomated Storage Scaling – There is no limit to the amount of data you can store in a DynamoDB table, and the service automatically allocates more storage, as you store more data using the DynamoDB write APIs; Provisioned Throughput – When creating a table, simply specify how much request capacity you require.

DynamoDB is an Amazon service which differs from other their services by allowing developers to purchase a service based on throughput, rather than storage. Although the database does not automatically scale, administrators can request more throughput and DynamoDB will spread the data and traffic over a number of servers using solid-state drives, predictable performance. Moreover, it offers integration with Hadoop via Elastic MapReduce.

DynamoDB pros:

• Scalable. There is no limit to the amount of data, and the service automatically allocate more storage.
• Flexible. Each data item may have different number of attributes. Multiple data types (strings, numbers, binary, and sets).
• Distributed. DynamoDB scales horizontally and seamlessly scales a single table over hundreds of servers.
• Cost effective. Allows more than 40 million database operations/month and pricing is based on throughput.
• Easy administration, etc.

DynamoDB cons:

• 64KB limit on row size
• 1Mb limit on querying
• secondary indexes are not supported
• joins are impossible
• deployable only on AWS
• extremely limited querying, especially, if you want to query non-indexed data, etc.

Dynamo is scalable NoSQL solution from AWS. However, not everybody knows how to utilize it at its best in order to make profit for their business.

In this post we try to look at pros and cons in comparison with other solutions and find use cases where DynamoDB works at its best.

So in NoSQL world there are particular requirements for dbs.

1. It has to accept and store massive amounts of data.
2. Scalability is a prior requirement. RDBMS is very hard to scale horizontally and there is particular point in time when it’s just reaching the limit. NoSQL in comparison is designed for horizontal scaling and could be scaled endlessly.
3. No relations, so query could be speeded up. However, because NoSQL means there is no ability to create complicated queries.

Also nobody can stop you from using RDBMS and NoSQL at the same time within the same app.

Why DynamoDB is good:

1. It has predictable speeds. Simply you just have to define throughput and use it. Expecting 100r/s just add more and you’re ready to go.
2. It is hosted on AWS premises and hence acting as a web service. For you that means you absolutely avoidу having administration headache. No more fleets of instances with Mongo master/slave nodes. No more complicated administration hell with load-balancers.
3. RedShift integration. That means you can export your DynamoDB table into Redshift and run complicated queries for data analytics.
4. Build-in CloudWatch monitoring. So you can watch your table performance in close to real time. This is a bit tricky and we should cover this in our next post about dynamo speed checking and speedometers.

So, if you decided to select this option, you could use AWS web-console or CLI. But these two are only good for monitoring tables. The ultimate tool is DynamoDB libraries. It gives you full access to all Dynamo features and most important part of it that you will be able to make Dynamo as part of your application through the code.

Below there are few code snippets which will give you understanding how to:

Create table

Add item

Edit table settings.

Add global index

Query table

Scan table

If you have any queries or problems with DynamoDB administration, please contact.

Amazon DynamoDB is a key-value and document database that delivers single-digit millisecond performance at any scale. It's a fully managed, multi-region, multi-active, durable database with built-in security, backup and restore, and in-memory caching for internet-scale applications. DynamoDB can handle more than 10 trillion requests per day and can support peaks of more than 20 million requests per second.

Many of the world's fastest growing businesses such as Lyft, Airbnb, and Redfin as well as enterprises such as Samsung, Toyota, and Capital One depend on the scale and performance of DynamoDB to support their mission-critical workloads.

Hundreds of thousands of AWS customers have chosen DynamoDB as their key-value and document database for mobile, web, gaming, ad tech, IoT, and other applications that need low-latency data access at any scale. Create a new table for your application and let DynamoDB handle the rest.

Benefits

Performance at scale

DynamoDB supports some of the world’s largest scale applications by providing consistent, single-digit millisecond response times at any scale. You can build applications with virtually unlimited throughput and storage. DynamoDB global tables replicate your data across multiple AWS Regions to give you fast, local access to data for your globally distributed applications. For use cases that require even faster access with microsecond latency, DynamoDB Accelerator (DAX) provides a fully managed in-memory cache.

No servers to manage

DynamoDB is serverless with no servers to provision, patch, or manage and no software to install, maintain, or operate. DynamoDB automatically scales tables up and down to adjust for capacity and maintain performance. Availability and fault tolerance are built in, eliminating the need to architect your applications for these capabilities. DynamoDB provides both provisioned and on-demand capacity modes so that you can optimize costs by specifying capacity per workload, or paying for only the resources you consume.

Enterprise ready

DynamoDB supports ACID transactions to enable you to build business-critical applications at scale. DynamoDB encrypts all data by default and provides fine-grained identity and access control on all your tables. You can create full backups of hundreds of terabytes of data instantly with no performance impact to your tables, and recover to any point in time in the preceding 35 days with no downtime. You also can export your DynamoDB table data to your data lake in Amazon S3 to perform analytics at any scale. DynamoDB is also backed by a service level agreement for guaranteed availability.

Applications

Serverless Web Apps

Build powerful web applications that automatically scale up and down. You don't need to maintain servers, and your applications have automated high availability.

Reference architecture: Sample code

Mobile Backends

Use DynamoDB and AWS AppSync to build interactive mobile and web apps with real-time updates, offline data access, and data sync with built-in conflict resolution.

Reference architecture: Sample code

Microservices

Build flexible and reusable microservices using DynamoDB as a serverless data store for consistent and fast performance.

Reference architecture: Sample code

Use cases

Ad Tech

Companies in the advertising technology (ad tech) vertical use DynamoDB as a key-value store for storing various kinds of marketing data, such as user profiles, user events, clicks, and visited links. Applicable use cases include real-time bidding (RTB), ad targeting, and attribution. These use cases require a high request rate (millions of requests per second), low predictable latency, and reliability. Companies use caching through DynamoDB Accelerator (DAX) when they have high read volumes or need submillisecond read latency. Increasingly, ad tech companies need to deploy their RTB and ad targeting platforms in more than one geographical AWS Region, which requires data replication between Regions.

Gaming

Companies in the gaming vertical use DynamoDB in all capabilities of game platforms, including game state, player data, session history, and leaderboards. The main benefits that these companies get from DynamoDB are its ability to scale reliably to millions of concurrent users and requests while ensuring consistently low latency measured in single-digit milliseconds. In addition, as a fully managed service, DynamoDB has no operational overhead, so game developers can focus on developing their games instead of managing databases. Also, as game developers are increasingly looking to expand from a single AWS Region to multiple AWS Regions, they can rely on DynamoDB global tables for multiple-Region, active-active replication of data.

Common use cases:

Dynamodb Consistent Write

• User profile stores in RTB and ad targeting
• User events, clickstreams, and impressions data store
• Metadata stores for assets
• Popular-item caches

Common use cases:

• Game states
• Player data stores
• Player session history data stores
• Leaderboards
  

Learn more about AWS databases for games »

The Pokémon Company migrated global configuration and time-to-live (TTL) data to Amazon DynamoDB, resulting in a 90 percent reduction in bot login attempts.

Read the case study »

Retail

Many companies in the retail space use common DynamoDB design patterns to deliver consistently low latency for mission-critical use cases. Being free from scaling concerns and operational burden is a key competitive advantage and an enabler for high-velocity, extreme-scaled events such as Amazon Prime Day, whose magnitudes are difficult to forecast. Scaling up and down allows these customers to pay only for the capacity they need and keeps precious technical resources focused on innovations rather than operations.

Banking and Finance

As companies in banking and finance build more cloud-native applications, they seek to use fully managed services to increase agility, reduce time to market, and minimize operational overhead. At the same time, they have to ensure the security, reliability, and high availability of their applications. As these companies expand their existing services that are backed by legacy mainframe systems, they find that legacy systems are unable to meet the scalability demands of their growing user base, new platforms such as mobile applications, and the resulting increases in traffic. To solve this problem, they replicate data from their mainframes to the cloud to offload the traffic.

Common use cases:

• Shopping carts
• Workflow engines
• Inventory tracking and fulfillment
• Customer profiles and accounts
  

Learn more about retail with AWS »

Common use cases:

• User transactions
• Event-driven transaction processing
• Fraud detection
• Mainframe offloading and change data capture
  

Learn more about AWS Financial Services »

Media and entertainment

Media and entertainment companies use DynamoDB when they require an extreme scale of throughput and concurrency, low latency, and reliability. DynamoDB scales elastically to handle the load and maintains low latency that is critical for real-time scenarios, such as video streaming and interactive content. In such scenarios, the number of concurrent users can reach millions, and no database handles that kind of concurrency as well as DynamoDB. Despite such high concurrency, the latency remains low, affording individual users optimal user experience, whether it involves retrieving their media, or participating in an interactive, real-time event. These companies use DynamoDB to address their scalability challenges and to keep their focus on feature development and not on database management.

Software and internet

One key commonality among software companies and many other DynamoDB customers is internet scale. These companies’ use cases require the ability to accommodate extreme concurrency, request rates, and spikes in traffic. This concurrency is measured in millions of users and connections, and request rates can easily reach millions per second. DynamoDB has a proven record of being able to handle internet-scale use cases and their requirements while maintaining consistent, single-digit millisecond latency. With global tables, DynamoDB customers can easily expand their applications to multiple AWS Regions for global reach and business continuity.

Common use cases:

• Media metadata stores
• User data stores
• Digital rights management data stores
  

Learn more about media & entertainment with AWS »

A+E Networks migrates to AWS, and it costs less than a latte to run their Access app for 1 day on a serverless architecture using Amazon DynamoDB.

Read the case study »

Common use cases:

• User content metadata stores
• Relationship graph data stores
• Metadata caches
• Ride-tracking data stores
• User, vehicle, and driver data stores
• User vocabulary data stores
  

Watch this video on Twitch to learn more »

Customers

Nike Digital migrated their large clusters of Cassandra to a fully managed Amazon DynamoDB, allowing more resources for better customer experience.

The U.S. Census Bureau uses DynamoDB to scale response collection on mobile or desktop, allowing people to participate in its decennial count online for the first time.

The Pokémon Company migrated global configuration and Time to Live (TTL) data to Amazon DynamoDB, resulting in a 90 percent reduction in bot login attempts.

Dynamodb Consistency Option

Samsung Electronics uses Amazon DynamoDB for their petabyte-sized mobile app backups, resulting in consistent high performance and cost savings.

A+E Networks migrates to AWS, and it costs less than a latte to run their cloud-native Access app for 1 day on a serverless architecture using Amazon DynamoDB.

Read the case study »

Netflix uses DynamoDB to run A/B testing that builds personalized streaming experiences for their 125+ million customers.

Capital One uses DynamoDB to reduce latency for their mobile applications by moving their mainframe transactions to a serverless architecture for unbound scale.

FanFight migrated its fantasy sports app to DynamoDB, allowing it to reduce costs by 50%, scale up to 1 million writes per second, and increase per-day revenue 4x.

Lyft leverages the scalability of DynamoDB for multiple data stores, including a ride-tracking system that stores GPS coordinates for all rides.

Tinder migrated user data to DynamoDB with zero downtime and leveraged the scalability of DynamoDB to meet the needs of their growing global user base.

Airbnb uses DynamoDB to scale their operations to a global user base, while optimizing their real-time processing workflows to analyze data.

Comcast uses DynamoDB to rapidly innovate and deploy updates to their XFINITY X1 video service running on more than 20 million devices.

Rockset's direct integration with DynamoDB, through DynamoDB Streams, enables them to iterate fast and gain huge time savings that benefit their customers.

Expedia built a rich, high-performance streaming system using DynamoDB to deliver fast, on-demand access to reference data sets for analytics.

Snap migrated their largest storage workload, Snapchat Stories, to DynamoDB and improved performance while reducing costs.

GE Aviation rearchitected their plotting and data-query application for cost savings, scalability, and performance using Amazon DynamoDB.

Amazon workflow engines run on DynamoDB for millisecond response times, allowing customers to get their orders faster.

Oath deployed GDPR compliance for their applications globally and leveraged Amazon DynamoDB global tables to enable data synchronization.

GumGum moved to Amazon DynamoDB from Apache Cassandra for better performance, cost savings, and maintenance reductions.

Redfin runs its business analytics operation on AWS, which allows it to innovate quickly with a small staff while managing billions of property records.

Learn more about performance at scale, serverless, and enterprise-ready features.

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Dynamodb Consistency

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Dynamodb Consistency Model

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