Amazon DynamoDBย vsย Google Cloud Bigtableย vsย Google Cloud Datastore

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Amazon DynamoDB
Amazon DynamoDB

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1.5K
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Google Cloud Bigtable
Google Cloud Bigtable

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Google Cloud Datastore
Google Cloud Datastore

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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 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 yearsโ€”it's the database driving major applications such as Google Analytics and Gmail.

What is 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.
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      What are some alternatives to Amazon DynamoDB, Google Cloud Bigtable, and Google Cloud Datastore?
      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
      Cassandra
      Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
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      How developers use Amazon DynamoDB, Google Cloud Bigtable, and Google Cloud Datastore
      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 ร–zรงelik
      Volkan ร–zรงelik uses Amazon DynamoDBAmazon DynamoDB

      zerotoherojs.com โ€™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 CommentBox.io
      CommentBox.io uses Google Cloud DatastoreGoogle Cloud Datastore

      This is our primary database, though most of our actual data is stored in static storage. This database houses the metadata necessary for indexing and finding static data.

      Avatar of nrise
      nrise uses Amazon DynamoDBAmazon DynamoDB

      ๋ช‡๋ช‡ ๋กœ๊ทธ๋Š” ํ˜„์žฌ AWS DynamoDB ์— ๊ธฐ๋ก๋˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ๊ฐœ์„ ์„ ํ†ตํ•ด mongodb ๋กœ ์˜ฎ๊ธธ ๊ณ„ํš์„ ํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์•„์ฃผ ๊ฐ„๋‹จํ•œ ๋ฐ์ดํ„ฐ๋ฅผ ์Œ“๋Š” ์šฉ๋„๋กœ๋Š” ๋‚˜์˜์ง€ ์•Š์Šต๋‹ˆ๋‹ค. ๋‹ค๋งŒ, ์ฟผ๋ฆฌ๊ฐ€ ์•„์ฃผ ์ œํ•œ์ ์ž…๋‹ˆ๋‹ค. ์‚ฌ์šฉํ•˜๊ธฐ ์ „์— ๋ฐ˜๋“œ์‹œ DynamoDB ์˜ ์ŠคํŽ™์„ ํ™•์ธํ•  ํ•„์š”๊ฐ€ ์žˆ์Šต๋‹ˆ๋‹ค.

      Avatar of papaver
      papaver uses Google Cloud DatastoreGoogle Cloud Datastore

      worked with a client that used datastore as their backend database. helped plan out their schema and architecture. loved the speed and simplicity.

      Avatar of HyperTrack
      HyperTrack uses Amazon DynamoDBAmazon DynamoDB

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

      Avatar of Giftstarter
      Giftstarter uses Google Cloud DatastoreGoogle Cloud Datastore

      We store our data in this store.

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