DBMS > Amazon DocumentDB vs. AntDB vs. Apache Impala vs. Microsoft Azure Cosmos DB vs. ObjectBox

System Properties Comparison Amazon DocumentDB vs. AntDB vs. Apache Impala vs. Microsoft Azure Cosmos DB vs. ObjectBox

Editorial information provided by DB-Engines

Name

Description

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

A scalable, multi-tenant, MPP-architectured RDBMS for OLTP and OLAP operations, highly compatible with Oracle

Analytic DBMS for Hadoop

Globally distributed, horizontally scalable, multi-model database service

Extremely fast embedded database for small devices, IoT and Mobile

Primary database model

Document store

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Object oriented DBMS

Secondary database models

Document store

Spatial DBMS

Time Series DBMS

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	0.25
Rank	#303	Overall
	#137	Relational DBMS

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

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

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Website

aws.amazon.com/documentdb

www.asiainfo.com/en_us/product_aisware_antdb_detail.html

impala.apache.org

azure.microsoft.com/services/cosmos-db

objectbox.io

Technical documentation

aws.amazon.com/documentdb/resources

impala.apache.org/impala-docs.html

learn.microsoft.com/azure/cosmos-db

docs.objectbox.io

Social network pages

Developer

AsiaInfo Technologies Limited

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Microsoft

ObjectBox Limited

Initial release

2019

2013

2014

2017

Current release

4.1.0, June 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

commercial

Open Source

Apache License 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++

C and C++

Server operating systems

hosted

Linux

hosted

Android
iOS
Linux
macOS
Windows

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.

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL2016 compliant

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

JDBC
MySQL protocol compliant
ODBC

JDBC
ODBC

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

Proprietary native API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

All languages supporting JDBC/ODBC

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

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

JavaScript

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

selectable replication factor

yes

Implicit feature of the cloud service

online/offline synchronization between client and server

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

query execution via MapReduce

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual 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

ACID

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.

yes

User concepts

Access control

Access rights for users and roles

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Access rights can be defined down to the item level

yes

More information provided by the system vendor

Specific characteristics

AntDB was initiated in 2008. On the core system of operators, AntDB provides online...
» more

Competitive advantages

HTAP mixed load: AntDB is a universal, enterprise-level distributed relational database,...
» more

Typical application scenarios

As the core software of large enterprise, AntDB supports multi-scenario deployment....
» more

Key customers

China Mobile, China Telecom, China Unicom, Aeon Life, China Mobile Tietong, CITIC...
» more

Market metrics

More than 1 billion subscribers in 24 provinces across China are served by AntDB...
» more

Licensing and pricing models

Certificates and licenses CMMI5 Certificate licensed by CMMI Institute IT Product...
» more

News

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23 April 2024

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15 February 2024

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14 November 2023

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.