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Learn MorePros of Amazon DynamoDB
Pros of Datomic Cloud
Pros of Google Cloud Bigtable
Pros of Amazon DynamoDB
- Predictable performance and cost62
- Scalable56
- Native JSON Support35
- AWS Free Tier21
- Fast7
- No sql3
- To store data3
- Serverless2
- No Stored procedures is GOOD2
- ORM with DynamoDBMapper1
- Elastic Scalability using on-demand mode1
- Elastic Scalability using autoscaling1
- DynamoDB Stream1
Pros of Datomic Cloud
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Pros of Google Cloud Bigtable
- High performance11
- Fully managed9
- High scalability5
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Cons of Amazon DynamoDB
Cons of Datomic Cloud
Cons of Google Cloud Bigtable
Cons of Amazon DynamoDB
- Only sequential access for paginate data4
- Scaling1
- Document Limit Size1
Cons of Datomic Cloud
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Cons of Google Cloud Bigtable
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What is Amazon DynamoDB?
With it , you can offload the administrative burden of operating and scaling a highly available distributed database cluster, while paying a low price for only what you use.
What is Datomic Cloud?
A transactional database with a flexible data model, elastic scaling, and rich queries. Datomic is designed from the ground up to run on AWS. Datomic leverages AWS technology, including DynamoDB, S3, EFS, and CloudFormation to provide a fully integrated solution.
What is Google Cloud Bigtable?
Google Cloud Bigtable offers you a fast, fully managed, massively scalable NoSQL database service that's ideal for web, mobile, and Internet of Things applications requiring terabytes to petabytes of data. Unlike comparable market offerings, Cloud Bigtable doesn't require you to sacrifice speed, scale, or cost efficiency when your applications grow. Cloud Bigtable has been battle-tested at Google for more than 10 years—it's the database driving major applications such as Google Analytics and Gmail.
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What companies use Amazon DynamoDB?
What companies use Datomic Cloud?
What companies use Google Cloud Bigtable?
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What tools integrate with Amazon DynamoDB?
What tools integrate with Datomic Cloud?
What tools integrate with Google Cloud Bigtable?
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What are some alternatives to Amazon DynamoDB, Datomic Cloud, and Google Cloud Bigtable?
Google Cloud Datastore
Use a managed, NoSQL, schemaless database for storing non-relational data. Cloud Datastore automatically scales as you need it and supports transactions as well as robust, SQL-like queries.
MongoDB
MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
Amazon SimpleDB
Developers simply store and query data items via web services requests and Amazon SimpleDB does the rest. Behind the scenes, Amazon SimpleDB creates and manages multiple geographically distributed replicas of your data automatically to enable high availability and data durability. Amazon SimpleDB provides a simple web services interface to create and store multiple data sets, query your data easily, and return the results. Your data is automatically indexed, making it easy to quickly find the information that you need. There is no need to pre-define a schema or change a schema if new data is added later. And scale-out is as simple as creating new domains, rather than building out new servers.
MySQL
The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
Amazon S3
Amazon Simple Storage Service provides a fully redundant data storage infrastructure for storing and retrieving any amount of data, at any time, from anywhere on the web