DBMS > eXtremeDB vs. Microsoft Azure Cosmos DB vs. OrientDB vs. Tarantool

System Properties Comparison eXtremeDB vs. Microsoft Azure Cosmos DB vs. OrientDB vs. Tarantool

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Editorial information provided by DB-Engines

Name

Description

Natively in-memory DBMS with options for persistency, high-availability and clustering

Globally distributed, horizontally scalable, multi-model database service

Multi-model DBMS (Document, Graph, Key/Value)

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

Primary database model

Relational DBMS
Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Document store
Graph DBMS
Key-value store

Document store
Key-value store
Relational DBMS

Secondary database models

Spatial DBMS

with Tarantool/GIS extension

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

Score	0.73
Rank	#227	Overall
	#104	Relational DBMS
	#18	Time Series DBMS

Score	29.85
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	3.27
Rank	#97	Overall
	#16	Document stores
	#6	Graph DBMS
	#15	Key-value stores

Score	1.67
Rank	#150	Overall
	#25	Document stores
	#25	Key-value stores
	#69	Relational DBMS

Website

www.mcobject.com

azure.microsoft.com/services/cosmos-db

orientdb.org

www.tarantool.io

Technical documentation

www.mcobject.com/docs/extremedb.htm

learn.microsoft.com/azure/cosmos-db

www.orientdb.com/docs/last/index.html

www.tarantool.io/en/doc

Developer

McObject

Microsoft

OrientDB LTD; CallidusCloud; SAP

Initial release

2001

2014

2010

2008

Current release

8.2, 2021

3.2.29, March 2024

2.10.0, May 2022

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

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 and C++

Java

C and C++

Server operating systems

AIX
HP-UX
Linux
macOS
Solaris
Windows

hosted

All OS with a Java JDK (>= JDK 6)

BSD
Linux
macOS

Data scheme

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

Typing

predefined data types such as float or date

yes

JSON types

yes

string, double, decimal, uuid, integer, blob, boolean, datetime

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.

support of XML interfaces available

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

yes

with the option: eXtremeSQL

SQL-like query language

SQL-like query language, no joins

Full-featured ANSI SQL support

APIs and other access methods

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

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

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

Open binary protocol

Supported programming languages

.Net
C
C#
C++
Java
Lua
Python
Scala

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

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

Server-side scripts

Stored procedures

yes

JavaScript

Java, Javascript

Lua, C and SQL stored procedures

Triggers

yes

by defining events

JavaScript

Hooks

yes, before/after data modification events, on replication events, client session events

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning / sharding

Sharding

Implicit feature of the cloud service

Sharding

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

Replication methods

Methods for redundantly storing data on multiple nodes

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

yes

Implicit feature of the cloud service

Multi-source replication

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

could be achieved with distributed queries

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

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

Foreign keys

Referential integrity

yes

relationship in graphs

yes

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

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

yes

yes, cooperative multitasking

Durability

Support for making data persistent

yes

yes, write ahead logging

In-memory capabilities

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

yes

yes, full featured in-memory storage engine with persistence

User concepts

Access control

Access rights can be defined down to the item level

Access rights for users and roles; record level security configurable

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

More information provided by the system vendor

Specific characteristics

eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Competitive advantages

eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
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Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
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Licensing and pricing models

For server use cases, there is a simple per-server license irrespective of the number...
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