DBMS > eXtremeDB vs. InfinityDB vs. RethinkDB vs. Sadas Engine

System Properties Comparison eXtremeDB vs. InfinityDB vs. RethinkDB vs. Sadas Engine

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Editorial information provided by DB-Engines

Name

Description

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

A Java embedded Key-Value Store which extends the Java Map interface

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Relational DBMS
Time Series DBMS

Key-value store

Document store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.80
Rank	#214	Overall
	#99	Relational DBMS
	#18	Time Series DBMS

Score	0.08
Rank	#365	Overall
	#55	Key-value stores

Score	2.66
Rank	#107	Overall
	#20	Document stores

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Website

Technical documentation

www.mcobject.com/docs/extremedb.htm

boilerbay.com/infinitydb/manual

rethinkdb.com/docs

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

McObject

Boiler Bay Inc.

The Linux Foundation

since July 2017

SADAS s.r.l.

Initial release

2001

2002

2009

2006

Current release

8.2, 2021

4.0

2.4.1, August 2020

8.0

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

commercial

free trial version available

Cloud-based only

Only available as a cloud service

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++

Server operating systems

AIX
HP-UX
Linux
macOS
Solaris
Windows

All OS with a Java VM

Linux
OS X
Windows

AIX
Linux
Windows

Data scheme

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

schema-free

yes

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

yes

string, binary, float, bool, date, geometry

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.

support of XML interfaces available

Secondary indexes

yes

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

yes

with the option: eXtremeSQL

yes

APIs and other access methods

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

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

JDBC
ODBC
Proprietary protocol

Supported programming languages

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

Java

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

by defining events

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning / sharding

none

Sharding

range based

horizontal partitioning

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

none

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate Consistency

Foreign keys

Referential integrity

yes

manual creation possible, using inversions based on multi-value capability

yes

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

yes

MVCC based

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

managed by 'Learn by Usage'

User concepts

Access control

yes

users and table-level permissions

Access rights for users, groups and roles according to SQL-standard

More information provided by the system vendor

Specific characteristics

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

Competitive advantages

eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more

Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more

Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more

Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
» more

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.

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