DBMS > Amazon DocumentDB vs. BaseX vs. HarperDB vs. MonetDB vs. ObjectBox

System Properties Comparison Amazon DocumentDB vs. BaseX vs. HarperDB vs. MonetDB vs. ObjectBox

Editorial information provided by DB-Engines

Name

Description

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

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

A relational database management system that stores data in columns

Extremely fast embedded database for small devices, IoT and Mobile

Primary database model

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	1.73
Rank	#142	Overall
	#4	Native XML DBMS

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Website

aws.amazon.com/documentdb

Technical documentation

aws.amazon.com/documentdb/resources

docs.basex.org

docs.harperdb.io/docs

www.monetdb.org/Documentation

docs.objectbox.io

Developer

BaseX GmbH

HarperDB

MonetDB BV

ObjectBox Limited

Initial release

2019

2007

2017

2004

2017

Current release

10.7, August 2023

3.1, August 2021

Dec2023 (11.49), December 2023

License

Commercial or Open Source

commercial

Open Source

BSD license

commercial

free community edition available

Open Source

Mozilla Public License 2.0

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

Java

Node.js

C and C++

Server operating systems

hosted

Linux
OS X
Windows

Linux
OS X

FreeBSD
Linux
OS X
Solaris
Windows

Android
iOS
Linux
macOS
Windows

Data scheme

schema-free

dynamic schema

yes

Typing

predefined data types such as float or date

yes

XQuery supports types

yes

JSON data 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

SQL

Support of SQL

SQL-like data manipulation statements

yes

SQL 2003 with some extensions

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Proprietary native API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

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

Custom Functions

since release 3.1

yes, in SQL, C, R

Triggers

yes

via events

yes

Partitioning methods

Methods for storing different data on different nodes

none

A table resides as a whole on one (or more) nodes in a cluster

Sharding via remote tables

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

none

yes

the nodes on which a table resides can be defined

none

Source-replica replication available in experimental status

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)

Consistency concepts

Methods to ensure consistency in a distributed system

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

multiple readers, single writer

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

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

Users with fine-grained authorization concept on 4 levels

Access rights for users and roles

fine grained access rights according to SQL-standard

yes

More information provided by the system vendor

News

The first On-Device Vector Database: ObjectBox 4.0
16 May 2024

Edge AI: The era of on-device AI
23 April 2024

In-Memory Database Use Cases
15 February 2024

Data Viewer for Objects – announcing ObjectBox Admin
14 November 2023

Vector Databases for Edge AI
9 August 2023

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

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