Amazon DynamoDB vs Azure Cosmos DB vs Google Cloud Bigtable

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Amazon DynamoDB
Amazon DynamoDB

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Azure Cosmos DB
Azure Cosmos DB

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Google Cloud Bigtable
Google Cloud Bigtable

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What is Amazon DynamoDB?

All data items are stored on Solid State Drives (SSDs), and are replicated across 3 Availability Zones for high availability and durability. With DynamoDB, 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 Azure Cosmos DB?

Azure DocumentDB is a fully managed NoSQL database service built for fast and predictable performance, high availability, elastic scaling, global distribution, and ease of development.

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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Why do developers choose Azure Cosmos DB?
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      What are some alternatives to Amazon DynamoDB, Azure Cosmos DB, 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 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.
      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
      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.
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      Decisions about Amazon DynamoDB, Azure Cosmos DB, and Google Cloud Bigtable
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      How developers use Amazon DynamoDB, Azure Cosmos DB, and Google Cloud Bigtable
      Avatar of Karma
      Karma uses Amazon DynamoDBAmazon DynamoDB

      For most of the stuff we use MySQL. We just use Amazon RDS. But for some stuff we use Amazon DynamoDB. We love DynamoDB. It's amazing. We store usage data in there, for example. I think we have close to seven or eight hundred million records in there and it's scaled like you don't even notice it. You never notice any performance degradation whatsoever. It's insane, and the last time I checked we were paying $150 bucks for that.

      Avatar of Volkan Özçelik
      Volkan Özçelik uses Amazon DynamoDBAmazon DynamoDB ’s userbase, and course details are stored in DynamoDB tables.

      The good thing about AWS DynamoDB is: For the amount of traffic that I have, it is free. It is highly-scalable, it is managed by Amazon, and it is pretty fast.

      It is, again, one less thing to worry about (when compared to managing your own MongoDB elsewhere).

      Avatar of CloudRepo
      CloudRepo uses Amazon DynamoDBAmazon DynamoDB

      We store customer metadata in DynamoDB. We decided to use Amazon DynamoDB because it was a fully managed, highly available solution. We didn't want to operate our own SQL server and we wanted to ensure that we built CloudRepo on high availability components so that we could pass that benefit back to our customers.

      Avatar of nrise
      nrise uses Amazon DynamoDBAmazon DynamoDB

      몇몇 로그는 현재 AWS DynamoDB 에 기록되고 있습니다. 개선을 통해 mongodb 로 옮길 계획을 하고 있습니다. 아주 간단한 데이터를 쌓는 용도로는 나쁘지 않습니다. 다만, 쿼리가 아주 제한적입니다. 사용하기 전에 반드시 DynamoDB 의 스펙을 확인할 필요가 있습니다.

      Avatar of Daniel Kovacs
      Daniel Kovacs uses Azure Cosmos DBAzure Cosmos DB

      If you need a document-based database with geo-redundancy (imagine AU-HU distance), this is the way to go.

      Avatar of HyperTrack
      HyperTrack uses Amazon DynamoDBAmazon DynamoDB

      To store device health records as it allows super fast writes and range queries.

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