DynamoDB is a great NoSQL storage solution
We use Amazon DynamoDB as a scalable solution for NoSQL related storage of data. It can take some getting used to how to work the primary …
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What is Amazon DynamoDB?
Amazon DynamoDB is a cloud-native, NoSQL, serverless database service.
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- Availability (70)9.494%
- Scalability (69)9.494%
- Performance (69)9.292%
- Security (70)9.090%
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What is Amazon DynamoDB?
Amazon DynamoDB is a NoSQL, fully managed, serverless
database boasting limitless scalability and single-digit millisecond latency
performance enabling customers to develop modern, microservice-based
applications through a simple API. DynamoDB’s
fully-managed service includes broad compliance standards, security
integration with AWS Identity and Access Management and numerous disaster
recovery services. With DynamoDB Global Tables, customers are offered a 99.999% highly
available, multi-Region, multi-active database supporting local reads and
writes for globally distributed users. DynamoDB provides cost management
features such as scale-to-zero, Time to Live (TTL) for aging data out, and
multiple pricing models including a free tier.
Amazon DynamoDB Features
NoSQL Databases Features
- Supported: Performance
- Supported: Availability
- Supported: Concurrency
- Supported: Security
- Supported: Scalability
- Supported: Data model flexibility
Additional Features
- Supported: Amazon DynamoDB is serverless allowing customers to scale instantly as workloads increase while providing an on-demand billing mode where they only pay for the resources consumed.
- Supported: Amazon DynamoDB provides up to a 99.999% SLA with zero downtime or maintenance windows.
Amazon DynamoDB Screenshots
Amazon DynamoDB Videos
AWS re:Invent 2019: Data modeling with Amazon DynamoDB (CMY304)
What is Amazon DynamoDB?
Amazon DynamoDB Competitors
Amazon DynamoDB Technical Details
| Deployment Types | Software as a Service (SaaS), Cloud, or Web-Based |
|---|---|
| Operating Systems | Unspecified |
| Mobile Application | No |
| Supported Countries | Global, North America, South America, Europe, Africa, Asia, Australia |
| Supported Languages | English, German, Spanish, Italian, Japanese, Portuguese, Chinese, Korean, French, Mandarin Chinese |
Frequently Asked Questions
Amazon DynamoDB is a cloud-native, NoSQL, serverless database service.
Reviewers rate Deployment model flexibility highest, with a score of 10.
The most common users of Amazon DynamoDB are from Enterprises (1,001+ employees).
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Reviews
(1-25 of 29)Companies can't remove reviews or game the system. Here's why
February 04, 2024
DynamoDB is a great NoSQL storage solution
We use Amazon DynamoDB as a scalable solution for NoSQL related storage of data. It can take some getting used to how to work the primary + secondary indexes to get the most benefit out of it, but for simple lookups and a basic data store it is a fantastic solution that allows us to remain agile and deploy quickly.
- Scalable data storage
- Solid NoSQL database
- Amazon's reliability
- Serverless solution
- Not as flexible as something like Firebase
- Has a learning curve for indexes
- Ties you into AWS infrastructure
November 14, 2023
If you need quick noSQL for serverless applications, DynamoDB is a good option to consider
Score 9 out of 10
Vetted Review
Verified User
We use DynamoDB for our low-latency data access for internal web-apps that require quick real-time information. It’s quite flexible for micro services and while it can be used in many different use cases we only use it for internal web apps, but could be recommended for mobile apps as well.
- Auto-scaling is done almost instantly, it’s magical.
- Works really well with serverless apps on AWS Lambdas
- It’s surprisingly transactional and support streams processing
- It’s not cheap at all. You must be careful with billing
- Not for large data
- Backup restoration is slow.
October 12, 2023
DynamoDB is a serverless, fully managed and NOSQL database.
The most beneficial aspect of Amazon DynamoDB is that it is completely managed by AWS. The developers should concentrate solely on the creation of the application and not on the infrastructure itself.
- fully manageable
- i can easily monitor operation in DynamoDB
- Secure
- Limited Storage option
- Estimating costs is difficult and time-consuming.
October 06, 2023
Best NoSQL Database Tool
We were building Amazon Alexa Game in which we used the DynamoDB for storing the user's data and leaderboard. Integration of Amazon DynamoDB was very smooth, there are pre-built examples are available and due to it is NoSQL, we can store any type of data without generation of the schema.
- It is NoSQL so storing data with very smooth
- Integration of it is very smooth
- It is Serverless so execution of it is very fast
- Integration of it apart from Amazon ecosystem is a bit hard
- Due to it is NoSQL, you can perform join and other operations
- Limited Storage option
October 06, 2023
Extremely Scalable - Full Marks for scalability
We are a fashion ecommerce company.
We have thousands and thousands of products in our inventory, with the use of Amazon DynamoDb it is easy and quick to fetch and insert products to the database.
Each and every information such as color, size etc is stored in the db and everything is super quick and efficient.
We have thousands and thousands of products in our inventory, with the use of Amazon DynamoDb it is easy and quick to fetch and insert products to the database.
Each and every information such as color, size etc is stored in the db and everything is super quick and efficient.
- Scalibilty - At times of very high traffic, Amazon DynamoDB is very easily scalable
- Latency is low hence product fetching and insertion is quick
- As it works in Nosql model hence it is very flexible when compared to RDBS systems
- Automated Backup and recovery is a complex feauture, this needs to be simple as it is one of the most important feauture
- Transactions limit needs to be increased, currently it is around 20-25 unique items
- Cost estimation is hard and challenging
September 26, 2023
Dynamo Db a unique NoSQL from Amazon
Dynamo DB is a respectable NoSQL database that can come handy while building web apps or mobile apps that need quick Realtime result displays. It can be powered with GraphQL for better queries as compared to Realtime data base of google. We mostly use it in cases where we might need realtime result displays in apps and web apps alongside the requirement for a little complex query that cannot be done in Google's counterpart.
- Quick Results
- Better Queries
- Version management for stored/ updated results
- Version management can be improved. It gets irritating at times
- Limited query language as compared to some other industry rivals
- Pricing is a little high
September 25, 2023
DynamoDB from a service providers perspective
Dynamo DB is my go-to option when requirements are for NoSQL DB that can scale very fast and have the options of global tables that can be used to support bigger infrastructures with key-value storage. The best thing is that it is a managed service so there is not a lot of overhead management required to keep it up to date.
- Scaling
- Global tables feature
- High performance
- Integration with other AWS services
- Cost can be lower.
- Complexity of working with global tables.
- Schema design challenges
September 20, 2023
My sweet and sweet experience with Amazon Dynamo DB
In our organization, we've leveraged Amazon DynamoDB in a revolutionary way: we've created a time-traveling historical database. Historians, archaeologists, and researchers often struggle to piece together the past from fragmented records, making it time-consuming and error-prone. DynamoDB changed the game.Our goal: a comprehensive historical database spanning centuries. We've digitized countless historical documents and artifacts, storing them in DynamoDB. Using DynamoDB's querying, historians can effortlessly analyze specific time periods or regions. It's like a time machine for historical data!But there's more. We've integrated DynamoDB with machine learning to fill gaps in records and predict future events, aiding archaeology and understanding ancient civilizations' trends.In essence, DynamoDB has transformed our historical research, unlocking the mysteries of the past. Thanks to DynamoDB, we're not just historians; we're time travelers!
- Highly scalable
- Low latency
- Fully Managed service
- NoSQL
- Expensive for small workload
- Lack of a Built-in Full-Text Search
- It is designed for single-table queries, and joining data from multiple tables can be challenging.
September 20, 2023
DynamoDB is fast, secure and easy to use.
Since this is a NoSQL DB that is able to sustain dingle-digit millisecond response times, it is very useful to implement architectures with delightful responsive UX to all our customers. Specific use cases are around: eCommerce carts where orders' documents are being assembled in DynamoDB before going to next steps of the purchasing process; multi-user interactive interfaces can benefit from the fast response to update dashboards, and interactions; and some public signage usages for arrival/departure boards can also be used for the display part of the process.
- Fast response
- Availability
- Security on rest
- Ease of use
- Cost model may not be easy to control and may lead to higher costs if not carefully planned
- Indexing may be a cost culprit when not planned, because it's not included on the data costs
- The Query Language may not fulfill everybody's expectations, as it has less features than those of competitors.
September 19, 2023
No SQL, Scalable Database
I use Amazon DynamoDB in my organization, EDII, to manage data across the Finance APIs.
- AI/ML
- User Data
- Logs
- SDK can be improved
- UI can be improved
September 19, 2023
Easy Serverless and Scalable
We use Amazon DynamoDBin two places.
1) Storing Information about the logs and the config data
2) Terraform state file
1) Storing Information about the logs and the config data
2) Terraform state file
- Fast Retrieval
- Serverless
- Excellent API
- UI can be improved
- Easy usable SDK
September 18, 2023
AWS DynamoDB use cases.
We used DynamoDB both alone and in combination with AWS Lambda functions. We used DynamoDB tables to store client data and combined them with DynamoDB streams to trigger lambda functions every time the table changed. This allowed us to run functions synchronously. Another use case was to run lambda functions at a specified UTC time zone, which was again stored in DynamoDB tables.
- Storing of Data.
- Running lambda functions to synchronously run jobs.
- Run asynchronous jobs.
- Store inconsistent data.
- It is hard to combine them with lambda functions if the job to be run will take longer than 30 seconds.
- It has some inconsistent behavior when fargate containers are involved.
September 18, 2023
Perfect for serverless transactional workloads
We have evaluated use cases for serverless applications ranging from simple key-value storage to complex "single table" designs for transactional data. The business requirement was to provide a straightforward, and well-performing data persistence layer for these applications, without the need of provisioning capacity. One particular use case models a language class booking system that is capable of handling bookings, cancellations of classes, and their respective seat bookings, models the teachers, teacher managers and the learners, and their actions too.
- Low latency read and write throughput
- Streaming data to consumers
- Transactions
- Secondary index management
- Migration tooling
- Point in time recovery performance
September 18, 2023
Dynamic scaling done easy by dynamoDB
We use AWS dynamo Db to store key value pairs for our business logic layer. We store details like last log in date, some config values and other non relational data.
- Integrates easily with other AWS infrastructure
- Easy to use interface on AWS console
- Scales easily with load
- Integrations with orms
- Migrations to other no sql databases
September 08, 2023
AWS DynamoDB Review
We used DynamoDB as our backend database. It was very effective and quick to use and we were able to get good results while using it.
- Provides Scalability
- Provides Access Control
- The item size limit of 400KB is something which we faced issue with once since we had a file of around 1-2MB that wasn't getting uploaded to the DB due to this issue
June 18, 2023
Just another review…
To save information on customers without having to deal with tables and columns, instead, you just pull the data from the person you want and continue. Like if a person is using a social network instead of having a table with a bunch of information we can locate customers easily.
- Pull Information easily.
- Fast and accessible.
- Being a elastic.
- Don’t see any, to be honest.
- Maybe implementing more tools.
August 16, 2019
Easy, Scalable, Reliable and Maintainable
Amazon DynamoDB is currently being used as one of our primary databases for several mobile and web applications. Key factors that directed us to choose Amazon DynamoDB are:
- It's part of the AWS family, and our entire platform is built on AWS and using a solution from AWS itself was one of the top priorities.
- Scalability and availability - Since its a managed solution we do not have to worry about scaling or the reliability of the database.
- Simple scalability and key-value storage.
- Building a real-time database using DynamoDB streams.
- Storing JSON data.
- Implementation was harder than relational databases.
- Querying is sometimes a nightmare.
- Backup and restore are not straightforward.
May 31, 2019
DynamoDB is a great No-SQL solution
DynamoDB is being used in multiple ways to store vast amounts of semi-structured data which need to be quickly accessible by specific parties. It allows us to easily add new fields/values and access them in an easy manner as projects require. The biggest benefit we see is the ability to add additional fields and not require the structure change of continuity.
- It's very easy to get started, creating a table with a partition/sort key and you're on your way.
- You can scale up and down your read/write IO as needed.
- You can store structured and unstructured data.
- It works great with Web Development as it's JSON based.
- There is a cost associated with creating indexes and being able to run queries.
- It would be nice to have a thick client to be able to connect and work with DynamoDB.
- It would be nice to be more aware of how DynamoDB functioned to be able to engineer towards optimization.
March 05, 2019
DynamoDB - Know you Absolutely Need it Before Committing
It was used as our primary data store for a link sharing and user profile-based application. We chose it for its speed and scalability as well as what we perceived beneficial pricing model. We knew that we wanted to use a NoSQL solution, and having one that was hosted by AWS seemed like an ideal fit.
- It's fast. VERY fast. We still house our data that needs to be accessed quickly here.
- It's a flexible NoSQL solution
- It has unlimited scalability and you can use only what you pay for.
- There is very minimal tooling for it compared to other mature solutions. You must go through the AWS dashboard to access what you need.
- The throughput model for charging can make it very difficult to effectively read and write. It's good for small consistent loads, but does not handle spikes and can not transferring large amounts of data. Once you have data in Dynamo, it's very difficult to transport it out at a reasonable cost - very annoying if you want to move data to a different type of storage.
- It gets expensive very quickly. We thought it would be cheap, but any kind of reasonable load will shoot your costs up beyond what you would have paid for other solutions.
- The data is very rigid. You must follow their model of declaring indexes and they can't be updated once the tables are created.
March 02, 2019
DyanmoDB scaling and backup
We use DynamoDB for our project VacationTracker. We decided to use DynamoDB because it was cheap and the latency between our AWS Serverless microservices and DynamoDB is less.
- Point-in-time recovery backup
- Auto-scaling
- Scaling horizontally
- Only pay for what you use, its good for a startup project.
- Price calculator, but for the startup project, it's free.
We are using DynamoDB with a simple, singular purpose - storing basic information for our customer base such as settings and configuration options. It's a quick and easy way for us to store and fetch this simple data, and since we have a very large presence within AWS already, it's a natural fit.
- Simple interface for setup
- Works well within an existing AWS ecosystem
- Fast
- Nothing, so long as you're using it with the intended purpose of a quick, reliable NOSQL DB
February 23, 2019
DynamoDB is *the* Non-Relational database for the Serverless age
We've been using Amazon DynamoDB since it was released in 2012. Previously, we used Amazon SimpleDB, which was much slower and slightly more difficult to work with than DynamoDB. DynamoDB is our "Source of Truth" for all data stored within my company, and is used to store all of our administrative information (such as connection details, FTP account information, and contact information), as well as the blog posts that we receive and process.
We have Lambda functions that write information to DynamoDB, which triggers other lambda functions to index that data in both SQL databases as well as Algolia for advanced searching and facet support.
DynamoDB helps us support the very random access patterns that we receive for content. Some days we process almost no stories, while other days we process hundreds of thousands of stories. With DynamoDB, we can automatically scale to whatever needs the day might have.
We have Lambda functions that write information to DynamoDB, which triggers other lambda functions to index that data in both SQL databases as well as Algolia for advanced searching and facet support.
DynamoDB helps us support the very random access patterns that we receive for content. Some days we process almost no stories, while other days we process hundreds of thousands of stories. With DynamoDB, we can automatically scale to whatever needs the day might have.
- Automatic Scaling (especially with the new on-demand capacity mode).
- Simple querying of massively large databases.
- Effortlessly store a relatively unlimited amount of information.
- Very cost effective for random access patterns.
- Complex searching (no support for case-insensitive or full-text search).
- Only supports up to two-key indexes.
- Requires choosing the indexes up-front when doing searches.
- Does not have an SQL compatible query front-end.
- No join-table support (requires putting all data into one table).
December 12, 2018
Impressive when used as designed; otherwise, risky
The engineering and data teams use DynamoDB to persist data for some of our services. We use it as an inexpensive, fully-managed key-value store. The business problem it primarily addresses is developer velocity. With DynamoDB, developers do not need to configure and manage a database; even RDS requires some more configuration and on-going maintenance than DynamoDB. DynamoDB is inexpensive; it allows developers to adhere to practices like one-database-per-service when building even small, temporary services.
- DynamoDB is fully-managed. In the early days, it lacked features like backups, and developers had to either implement some of their own backup functionality or live dangerously. Today, DynamoDB's claim to be fully-managed is more credible. Backups can be configured through the console. Table capacity does not even need to be planned anymore; you can scale (and pay) on-demand.
- DynamoDB is inexpensive for some use-cases. In particular, DynamoDB is very inexpensive when you create a datastore for a low-volume micro-service, or a stateful background job. DynamoDB is much less expensive than RDS or Elasticache for these use-cases, and it allows developers to design systems without worrying about cost.
- DynamoDB is fast when used for the use-cases it was designed for.
- DynamoDB supports the development experience and testing reasonably well. AWS provides an official DynamoDB image that can be used in tests locally or in CI.
- Capacity planning can be difficult, but it is probably a worthwhile exercise in itself. However, today you can scale tables on-demand without capacity planning.
- Migrations can be slow and difficult. If you need to change your schema (e.g., add a secondary index) after you have written a large volume of data to the table or after consumers of the data are live, migrating can be expensive. Tooling for DynamoDB migrations is less mature than tools for migrating other datastores.
- The API is complicated, and third-party wrappers, like PynamoDB, are immature.
- Scanning tables is slow and expensive. It is important to anticipate all of the types of queries you will need to support and design your schema accordingly.
May 03, 2018
NoSQL is DynamoDB. Always.
Amazon DynamoDB is just the best NoSQL database. I really love the interface and scalability. The best part is vertical scaling. It's just very affordable and making queries is very easy. Using Amazon's Boto3 API is a good source for proxying queries and requests. Third party module and support are good too. I am really using because they are adding new indexes to the table, making it fast and intuitive for prototyping.
I feel they lack Amazon's strong type checking. So I feel they need to work a bit on this part. I've also used DynamoDB on the local system but they need to add more flexibility to the local system. Overall, I feel if you are planning 1 million/min queries then it's perfect for your usage.
I feel they lack Amazon's strong type checking. So I feel they need to work a bit on this part. I've also used DynamoDB on the local system but they need to add more flexibility to the local system. Overall, I feel if you are planning 1 million/min queries then it's perfect for your usage.
- The usage of hash and range keys to retrieve flat objects is a plus
- Very easy usage with CloudFront and Elastic Beanstalk.
- Using Amazon CloudWatch monitoring on Amazon DynamoDB is always a good point.
- I feel they need to improve in strong type checking
- The relational database is tough to migrate so this might be a no for you.
- I feel the local setup is a good idea for testing but some improvements are sorely needed.
October 13, 2017
An expensive coffin for you NoSQL data.
We use dynamodb for to store and track millions of email messages sent by our sass product. Each email is unique, and in order to maintain a full record of our transactions with clients, we store, and recall each message that was ever sent using dynamodb. Because of the sheer scale and data size requirements it makes it very difficult to use traditional methods of recall, especially when you want the actual text of the email to be part of the database and not stored in offline storage.
- Recall on primary hashes is very fast, with HTTP latency over the network we were regularly able to call up records in the 20ms range from a database of millions of records
- Like other NoSQL databases Dynamo lets you easily and quickly add fields to each record without having to define a full schema.
- Pricing is quite affordable as long as you are efficient with your queries. You really need to be doing hash lookups rather than scans since Amazon charges you per record accessed.
- Query "language" leaves much to be desired. If you're coming from a database like MongoDB or SQL you'll find it extremely difficult to get data back out of the system without breaking the bank.
- Because querying is poor, often the only way to get data out of arbitrary fields is by scanning the records – but the pricing model for this is cost prohibitive. This means you frequently need additional architecture to keep track of where data is stored in the hash table. While this is an issue for lots of NoSQL database, DynamoDB is probably the worst offender I've used to date because of the pricing model.
- Amazon does offer a local version of DynamoDB you can run in development, but its an extremely clunky and very hard to integrate into any kind of continuous integration.