DBMS > ArcadeDB vs. atoti vs. Axibase vs. Microsoft Azure Cosmos DB vs. RDF4J

System Properties Comparison ArcadeDB vs. atoti vs. Axibase vs. Microsoft Azure Cosmos DB vs. RDF4J

Editorial information provided by DB-Engines

Name

Description

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

Globally distributed, horizontally scalable, multi-model database service

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Object oriented DBMS

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

RDF store

Secondary database models

Spatial DBMS

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

Score	0.10
Rank	#358	Overall
	#48	Document stores
	#38	Graph DBMS
	#52	Key-value stores
	#35	Time Series DBMS

Score	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

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

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Website

arcadedb.com

atoti.io

axibase.com/docs/atsd/finance

azure.microsoft.com/services/cosmos-db

rdf4j.org

Technical documentation

docs.arcadedb.com

docs.atoti.io

learn.microsoft.com/azure/cosmos-db

rdf4j.org/documentation

Developer

Arcade Data

ActiveViam

Axibase Corporation

Microsoft

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2021

2013

2014

2004

Current release

September 2021

15585

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free versions available

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

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

Server operating systems

All OS with a Java VM

Linux

hosted

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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

SQL-like query language, no joins

Multidimensional Expressions (MDX)

SQL-like query language

APIs and other access methods

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

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

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

Java

Go
Java
PHP
Python
R
Ruby

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

Java
PHP
Python

Server-side scripts

Stored procedures

Python

yes

JavaScript

yes

Triggers

yes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Implicit feature of the cloud service

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Foreign keys

Referential integrity

yes

relationship in graphs

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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 can be defined down to the item level

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