DBMS > Google Cloud Bigtable vs. Google Cloud Firestore vs. Microsoft Azure Cosmos DB vs. OrigoDB vs. SpaceTime

System Properties Comparison Google Cloud Bigtable vs. Google Cloud Firestore vs. Microsoft Azure Cosmos DB vs. OrigoDB vs. SpaceTime

Editorial information provided by DB-Engines

Name

Description

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Globally distributed, horizontally scalable, multi-model database service

A fully ACID in-memory object graph database

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Primary database model

Key-value store
Wide column store

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Document store
Object oriented DBMS

Spatial DBMS

Secondary database models

Spatial DBMS

Relational DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	0.03
Rank	#392	Overall
	#8	Spatial DBMS

Website

cloud.google.com/bigtable

firebase.google.com/products/firestore

azure.microsoft.com/services/cosmos-db

origodb.com

www.mireo.com/spacetime

Technical documentation

cloud.google.com/bigtable/docs

firebase.google.com/docs/firestore

learn.microsoft.com/azure/cosmos-db

origodb.com/docs

Developer

Google

Microsoft

Robert Friberg et al

Mireo

Initial release

2015

2017

2014

2009

under the name LiveDB

2020

License

Commercial or Open Source

commercial

Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Server operating systems

hosted

Linux
Windows

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

User defined using .NET types and collections

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

can be achieved using .NET

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

A subset of ANSI SQL is implemented

APIs and other access methods

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

.NET Client API
HTTP API
LINQ

RESTful HTTP API

Supported programming languages

C#
C++
Go
Java
JavaScript (Node.js)
Python

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

.Net

C#
C++
Python

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

JavaScript

yes

Triggers

yes, with Cloud Functions

JavaScript

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning

client side managed; servers are not synchronized

Fixed-grid hypercubes

Replication methods

Methods for redundantly storing data on multiple nodes

Internal replication in Colossus, and regional replication between two clusters in different zones

Multi-source replication

yes

Implicit feature of the cloud service

Source-replica replication

Real-time block device replication (DRBD)

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

depending on model

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Atomic single-row operations

yes

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

Access rights can be defined down to the item level

Role based authorization

yes

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