DBMS > Amazon DocumentDB vs. HugeGraph vs. Interbase vs. MonetDB vs. RocksDB

System Properties Comparison Amazon DocumentDB vs. HugeGraph vs. Interbase vs. MonetDB vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

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

A fast-speed and highly-scalable Graph DBMS

Light-weight proven RDBMS

originally from Borland

A relational database management system that stores data in columns

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	1.91
Rank	#131	Overall
	#24	Document stores

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	4.08
Rank	#75	Overall
	#41	Relational DBMS

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

aws.amazon.com/documentdb

github.com/hugegraph
hugegraph.apache.org

www.embarcadero.com/products/interbase

www.monetdb.org

rocksdb.org

Technical documentation

aws.amazon.com/documentdb/resources

hugegraph.apache.org/docs

docs.embarcadero.com/products/interbase

www.monetdb.org/Documentation

github.com/facebook/rocksdb/wiki

Developer

Baidu

Embarcadero

MonetDB BV

Facebook, Inc.

Initial release

2019

2018

1984

2004

2013

Current release

0.9

InterBase 2020, December 2019

Dec2023 (11.49), December 2023

9.2.1, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Open Source

Mozilla Public License 2.0

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

hosted

Linux
macOS
Unix

Android
iOS
Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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.

export as XML data possible

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

yes

SQL 2003 with some extensions

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

Java API
RESTful HTTP API
TinkerPop Gremlin

ADO.NET
JDBC
ODBC

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

C++ API
Java API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

Groovy
Java
Python

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

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

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

yes

Interbase procedure and trigger language

yes, in SQL, C, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

depending on used storage backend, e.g. Cassandra and HBase

none

Sharding via remote tables

horizontal partitioning

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

depending on used storage backend, e.g. Cassandra and HBase

Interbase Change Views

none

Source-replica replication available in experimental status

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

edges in graph

yes

Transaction concepts

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

Atomic single-document operations

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

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

Users, roles and permissions

fine grained access rights according to SQL-standard

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