Software Alternatives, Accelerators & Startups

DynamoDB VS AWS Lambda

Compare DynamoDB VS AWS Lambda and see what are their differences

DynamoDB logo DynamoDB

Amazon DynamoDB is a fast and flexible NoSQL database service for all applications that need consistent, single-digit millisecond latency at any scale. It is a fully managed cloud database and supports both document and key-value store models.

AWS Lambda logo AWS Lambda

Automatic, event-driven compute service
  • DynamoDB Landing page
    Landing page //
    2023-03-18
  • AWS Lambda Landing page
    Landing page //
    2023-04-29

DynamoDB features and specs

  • Scalability
    DynamoDB automatically scales up and down to handle your application's needs, with no intervention required. This allows for easy handling of traffic spikes and growth over time.
  • Performance
    With its fast, predictable performance at any scale, DynamoDB ensures low-latency responses, even with large volumes of data.
  • Fully Managed
    As a fully managed service, DynamoDB handles hardware provisioning, setup, configuration, replication, software patching, and backups, letting you focus on your application.
  • Flexible Data Model
    DynamoDB supports both document and key-value store models, providing flexibility in how you structure your data.
  • Security
    DynamoDB integrates with AWS Identity and Access Management (IAM) to provide fine-grained access control and encrypts data at rest and in transit.
  • Global Tables
    You can create multi-region, fully replicated tables for high availability and globally distributed apps with low latency reads and writes.
  • Event-Driven Architecture
    DynamoDB integrates with AWS Lambda for automatic triggering and the creation of event-driven architectures.

Possible disadvantages of DynamoDB

  • Pricing Complexity
    DynamoDB's pricing model, which charges based on read and write capacity units, storage, and data transfer, can be complex and difficult to predict.
  • Limited Query Capabilities
    DynamoDB does not support complex queries as well as traditional SQL databases. Querying capabilities are limited primarily to primary key attributes.
  • Secondary Indexes
    While DynamoDB supports secondary indexes, their use can be limited and complex to manage effectively compared to relational databases.
  • Consistency
    DynamoDB offers eventual consistency by default. While strongly consistent reads are available, they can be more expensive and slower.
  • Data Size Limitations
    Each item in a DynamoDB table must be 400KB or less, limiting the amount of data you can store in a single item.
  • Vendor Lock-In
    Using DynamoDB heavily ties your application to AWS, which can be a downside if you want to maintain flexibility in your cloud infrastructure choices.

AWS Lambda features and specs

  • Scalability
    AWS Lambda automatically scales your application by running your code in response to each trigger. This means no manual intervention is required to handle varying levels of traffic.
  • Cost-effectiveness
    You only pay for the compute time you consume. Billing is metered in increments of 100 milliseconds and you are not charged when your code is not running.
  • Reduced Operations Overhead
    AWS Lambda abstracts the infrastructure management layer, so there is no need to manage or provision servers. This allows you to focus more on writing code for your applications.
  • Flexibility
    Supports multiple programming languages such as Python, Node.js, Ruby, Java, Go, and .NET, which allows you to use the language you are most comfortable with.
  • Integration with Other AWS Services
    Seamlessly integrates with many other AWS services such as S3, DynamoDB, RDS, SNS, and more, making it versatile and highly functional.
  • Automatic Scaling and Load Balancing
    Handles thousands of concurrent requests without managing the scaling yourself, making it suitable for applications requiring high availability and reliability.

Possible disadvantages of AWS Lambda

  • Cold Start Latency
    The first request to a Lambda function after it has been idle for a certain period can take longer to execute. This is referred to as a 'cold start' and can impact performance.
  • Resource Limits
    Lambda has defined limits, such as a maximum execution timeout of 15 minutes, memory allocation ranging from 128 MB to 10,240 MB, and temporary storage up to 512 MB.
  • Vendor Lock-in
    Using AWS Lambda ties you into the AWS ecosystem, making it difficult to migrate to another cloud provider or an on-premises solution without significant modifications to your application.
  • Complexity of Debugging
    Debugging and monitoring distributed, serverless applications can be more complex compared to traditional applications due to the lack of direct access to the underlying infrastructure.
  • Cold Start Issues with VPC
    When Lambda functions are configured to access resources within a Virtual Private Cloud (VPC), the cold start latency can be exacerbated due to additional VPC networking overhead.
  • Limited Execution Control
    AWS Lambda is designed for stateless, short-running tasks and may not be suitable for long-running processes or tasks requiring complex orchestration.

Analysis of DynamoDB

Overall verdict

  • DynamoDB is a highly recommended NoSQL database option, especially for applications and services built on the AWS ecosystem. Its ability to handle large-scale applications with minimal manual configuration and strong performance metrics makes it an excellent choice for developers seeking a reliable and efficient database solution.

Why this product is good

  • DynamoDB is praised for its fully managed nature, allowing developers to focus on application development rather than complex infrastructure management. It offers high scalability with seamless data partitioning, replicates data across multiple availability zones, and provides built-in security features. DynamoDB is particularly effective for applications requiring rapid background processing of large data sets, with quick read and write performance due to its low-latency nature. Its serverless architecture ensures automatic scaling, so it adjusts easily to accommodate changing workloads without any manual intervention.

Recommended for

  • Applications requiring high availability and scalability
  • Real-time analytics and caching
  • Web applications with unpredictable workload patterns
  • Mobile backends and serverless applications
  • IoT applications needing fast and frequent data access

Analysis of AWS Lambda

Overall verdict

  • AWS Lambda is a strong choice for developers looking for scalable, event-driven applications with minimal management overhead. It is particularly beneficial for applications that experience intermittent traffic or unpredictable workloads.

Why this product is good

  • AWS Lambda is a popular serverless computing service because it allows users to run code without provisioning or managing servers. It automatically scales applications by running code in response to triggers such as HTTP requests, changes in data, or system events. This can significantly reduce operational overhead and costs, as you only pay for the compute time you consume.

Recommended for

  • Developers building microservices or serverless applications.
  • Companies looking to reduce infrastructure management.
  • Startups wanting to quickly deploy applications with limited operational costs.
  • Organizations needing to integrate with other AWS services for a comprehensive solution.
  • Projects with unpredictable or variable workloads that require automatic scaling.

DynamoDB videos

#13 - Amazon DynamoDB Basics In Under 5 Minutes [Tutorial For Beginners]

More videos:

  • Review - AWS re:Invent 2018: Amazon DynamoDB Deep Dive: Advanced Design Patterns for DynamoDB (DAT401)
  • Review - What is Amazon DynamoDB?

AWS Lambda videos

AWS Lambda Vs EC2 | Serverless Vs EC2 | EC2 Alternatives

More videos:

  • Tutorial - AWS Lambda Tutorial | AWS Tutorial for Beginners | Intro to AWS Lambda | AWS Training | Edureka
  • Tutorial - AWS Lambda | What is AWS Lambda | AWS Lambda Tutorial for Beginners | Intellipaat

Category Popularity

0-100% (relative to DynamoDB and AWS Lambda)
Databases
100 100%
0% 0
Cloud Computing
12 12%
88% 88
NoSQL Databases
100 100%
0% 0
Cloud Hosting
14 14%
86% 86

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare DynamoDB and AWS Lambda

DynamoDB Reviews

Top 5 Dynobase alternatives you should know about - March 2025 Review
Dynomate offers a comprehensive solution with native AWS SSO support, advanced multi-tab functionality, and Git-based collaboration features. NoSQL Workbench is a valuable free tool from AWS, excellent for designing and visualizing data models. The JetBrains DynamoDB Plugin brings DynamoDB into your IDE with helpful autocomplete and query-saving features.
Source: www.dynomate.io
9 Best MongoDB alternatives in 2019
Amazon DynamoDB is a nonrelational database. This database system provides consistent latency and offers built-in security, and in-memory caching. DynamoDB is a serverless database which scales automatically and backs up your data for protection
Source: www.guru99.com

AWS Lambda Reviews

Top 7 Firebase Alternatives for App Development in 2024
AWS Lambda is suitable for applications with varying workloads and those already using the AWS ecosystem.
Source: signoz.io

Social recommendations and mentions

Based on our record, AWS Lambda should be more popular than DynamoDB. It has been mentiond 277 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

DynamoDB mentions (121)

  • Serverless Backend: A New Era for Developers
    Database: It helps storing, managing and retriving data in a structured manner (e.g. NeonDB, PlanetScale, DynamoDB). - Source: dev.to / 6 days ago
  • Quarkus 3 application on AWS Lambda- Part 1 Introduction to the sample application and first Lambda performance measurements
    In this application, we will create products and retrieve them by their ID and use Amazon DynamoDB as a NoSQL database for the persistence layer. We use Amazon API Gateway which makes it easy for developers to create, publish, maintain, monitor and secure APIs and AWS Lambda to execute code without the need to provision or manage servers. We also use AWS SAM, which provides a short syntax optimised for defining... - Source: dev.to / about 1 month ago
  • Deploy AWS Lambda Functions and Amazon DynamoDB with AWS CDK on LocalStack
    In this example, we need to set up two AWS Lambda, AWS Secrets Manager and Amazon DynamoDB resources. - Source: dev.to / 2 months ago
  • Query Optimization and Performance in DynamoDB: Partition Key and Sort Key
    Amazon DynamoDB revolutionized the NoSQL database world with its flexible data model and high performance. At the core of its architecture, we find two fundamental concepts: Partition Key (PK) and Sort Key (SK). This article explores how these elements not only structure data but also significantly impact application performance and scalability. - Source: dev.to / 4 months ago
  • Automate Email Processing using Event Driven Architecture and Generative AI
    ExtractDataFunction:uses Langchain and LangSmith to validate and extract structured JSON info through Bedrock and Sonnet 3.5 v2 and then store it in DynamoDB for later use. - Source: dev.to / 4 months ago
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AWS Lambda mentions (277)

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What are some alternatives?

When comparing DynamoDB and AWS Lambda, you can also consider the following products

MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.

Amazon S3 - Amazon S3 is an object storage where users can store data from their business on a safe, cloud-based platform. Amazon S3 operates in 54 availability zones within 18 graphic regions and 1 local region.

Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.

Amazon API Gateway - Create, publish, maintain, monitor, and secure APIs at any scale

Google App Engine - A powerful platform to build web and mobile apps that scale automatically.

Google Cloud Functions - A serverless platform for building event-based microservices.