DBMS > eXtremeDB vs. Microsoft Azure Cosmos DB vs. OrientDB vs. Prometheus vs. Solr

System Properties Comparison eXtremeDB vs. Microsoft Azure Cosmos DB vs. OrientDB vs. Prometheus vs. Solr

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)

Open-source Time Series DBMS and monitoring system

A widely used distributed, scalable search engine based on Apache Lucene

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

Time Series DBMS

Search engine

Secondary database models

Spatial DBMS

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

Score	0.74
Rank	#223	Overall
	#103	Relational DBMS
	#18	Time Series DBMS

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

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Website

www.mcobject.com

azure.microsoft.com/services/cosmos-db

orientdb.org

prometheus.io

solr.apache.org

Technical documentation

www.mcobject.com/docs/extremedb.htm

learn.microsoft.com/azure/cosmos-db

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

prometheus.io/docs

solr.apache.org/resources.html

Developer

McObject

Microsoft

OrientDB LTD; CallidusCloud; SAP

Apache Software Foundation

Initial release

2001

2014

2010

2015

2006

Current release

8.2, 2021

3.2.29, March 2024

9.6.0, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

Apache 2.0

Open Source

Apache Version 2

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

Server operating systems

AIX
HP-UX
Linux
macOS
Solaris
Windows

hosted

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

Linux
Windows

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

yes

schema-free

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

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

yes

JSON types

yes

Numeric data only

yes

supports customizable data types and automatic typing

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

Import of XML data possible

yes

Secondary indexes

yes

All properties auto-indexed by default

yes

All search fields are automatically indexed

SQL

Support of SQL

yes

with the option: eXtremeSQL

SQL-like query language

SQL-like query language, no joins

Solr Parallel SQL Interface

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

RESTful HTTP/JSON API

Java API
RESTful HTTP/JSON API

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

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

JavaScript

Java, Javascript

Java plugins

Triggers

yes

by defining events

JavaScript

Hooks

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning / sharding

Sharding

Implicit feature of the cloud service

Sharding

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

yes

by Federation

yes

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

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

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

none

Eventual 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

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

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 can be defined down to the item level

Access rights for users and roles; record level security configurable

yes

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