Amazon DocumentDB vs Google Cloud Bigtable

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Amazon DocumentDB

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Google Cloud Bigtable

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Google Cloud Bigtable vs Amazon DocumentDB: What are the differences?

Developers describe Google Cloud Bigtable as "The same database that powers Google Search, Gmail and Analytics". 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. On the other hand, Amazon DocumentDB is detailed as "Fast, scalable, highly available MongoDB-compatible database service". Amazon DocumentDB is a non-relational database service designed from the ground-up to give you the performance, scalability, and availability you need when operating mission-critical MongoDB workloads at scale. In Amazon DocumentDB, the storage and compute are decoupled, allowing each to scale independently, and you can increase the read capacity to millions of requests per second by adding up to 15 low latency read replicas in minutes, regardless of the size of your data.

Google Cloud Bigtable and Amazon DocumentDB can be categorized as "NoSQL Database as a Service" tools.

Some of the features offered by Google Cloud Bigtable are:

  • Unmatched Performance: Single-digit millisecond latency and over 2X the performance per dollar of unmanaged NoSQL alternatives.
  • Open Source Interface: Because Cloud Bigtable is accessed through the HBase API, it is natively integrated with much of the existing big data and Hadoop ecosystem and supports Google’s big data products. Additionally, data can be imported from or exported to existing HBase clusters through simple bulk ingestion tools using industry-standard formats.
  • Low Cost: By providing a fully managed service and exceptional efficiency, Cloud Bigtable’s total cost of ownership is less than half the cost of its direct competition.

On the other hand, Amazon DocumentDB provides the following key features:

  • MongoDB-compatible
  • Fully managed
  • Performance at scale
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Pros of Amazon DocumentDB
Pros of Google Cloud Bigtable
  • 0
    Storage elasticity
  • 0
    Scalable
  • 0
    Easy Setup
  • 11
    High performance
  • 9
    Fully managed
  • 5
    High scalability

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What is Amazon DocumentDB?

Amazon DocumentDB is a non-relational database service designed from the ground-up to give you the performance, scalability, and availability you need when operating mission-critical MongoDB workloads at scale. In Amazon DocumentDB, the storage and compute are decoupled, allowing each to scale independently, and you can increase the read capacity to millions of requests per second by adding up to 15 low latency read replicas in minutes, regardless of the size of your data.

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 DocumentDB?
What companies use Google Cloud Bigtable?
See which teams inside your own company are using Amazon DocumentDB or Google Cloud Bigtable.
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What tools integrate with Amazon DocumentDB?
What tools integrate with Google Cloud Bigtable?

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What are some alternatives to Amazon DocumentDB and Google Cloud Bigtable?
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.
MongoDB Atlas
MongoDB Atlas is a global cloud database service built and run by the team behind MongoDB. Enjoy the flexibility and scalability of a document database, with the ease and automation of a fully managed service on your preferred cloud.
Elasticsearch
Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).
Atlas
Atlas is one foundation to manage and provide visibility to your servers, containers, VMs, configuration management, service discovery, and additional operations services.
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.
See all alternatives