DBMS > Amazon DocumentDB vs. GBase vs. Microsoft Azure Cosmos DB vs. StarRocks

System Properties Comparison Amazon DocumentDB vs. GBase vs. Microsoft Azure Cosmos DB vs. StarRocks

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Editorial information provided by DB-Engines

Name

Description

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

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Globally distributed, horizontally scalable, multi-model database service

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

Primary database model

Document store

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1.04
Rank	#189	Overall
	#88	Relational DBMS

Website

aws.amazon.com/documentdb

www.gbase.cn

azure.microsoft.com/services/cosmos-db

www.starrocks.io

Technical documentation

aws.amazon.com/documentdb/resources

learn.microsoft.com/azure/cosmos-db

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

Developer

General Data Technology Co., Ltd.

Microsoft

The Linux Foundation

since Feb 2023

Initial release

2019

2004

2014

2020

Current release

GBase 8a, GBase 8s, GBase 8c

2.5.3, March 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

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, Java, Python

C++, Java

Server operating systems

hosted

Linux

hosted

Linux

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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.

yes

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

Standard with numerous extensions

SQL-like query language

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

ADO.NET
C API
JDBC
ODBC

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

JDBC
MySQL protocol

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

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

Java

Server-side scripts

Stored procedures

user defined functions

JavaScript

user defined functions

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

Implicit feature of the cloud service

horizontal partitioning (by range and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

Implicit feature of the cloud service

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

Immediate 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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

User concepts

Access control

Access rights for users and roles

yes

Access rights can be defined down to the item level

Role based access control and fine grained access rights

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