DBMS > Amazon DocumentDB vs. Lovefield vs. Microsoft Azure Cosmos DB vs. Sequoiadb

System Properties Comparison Amazon DocumentDB vs. Lovefield vs. Microsoft Azure Cosmos DB vs. Sequoiadb

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Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

Embeddable relational database for web apps written in pure JavaScript

Globally distributed, horizontally scalable, multi-model database service

NewSQL database with distributed OLTP and SQL

Primary database model

Document store

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Document store
Relational DBMS

Secondary database models

Spatial DBMS

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

Score	1.91
Rank	#131	Overall
	#24	Document stores

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

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

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Website

aws.amazon.com/documentdb

google.github.io/lovefield

azure.microsoft.com/services/cosmos-db

www.sequoiadb.com

Technical documentation

aws.amazon.com/documentdb/resources

github.com/google/lovefield/blob/master/docs/spec_index.md

learn.microsoft.com/azure/cosmos-db

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Google

Microsoft

Sequoiadb Ltd.

Initial release

2019

2014

2013

Current release

2.1.12, February 2017

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

Server: AGPL; Client: Apache V2

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

JavaScript

C++

Server operating systems

hosted

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

hosted

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

yes

oid, date, timestamp, binary, regex

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.

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

SQL-like query language

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

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

proprietary protocol using JSON

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

JavaScript

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

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

JavaScript

Triggers

Using read-only observers

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

none

yes

Implicit feature of the cloud service

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

Atomic single-document operations

ACID

Multi-item ACID transactions with snapshot isolation within a partition

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

Access rights for users and roles

Access rights can be defined down to the item level

simple password-based access control

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