DBMS > EsgynDB vs. NuoDB vs. Oracle Coherence vs. Realm vs. Solr

System Properties Comparison EsgynDB vs. NuoDB vs. Oracle Coherence vs. Realm vs. Solr

Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Oracles in-memory data grid solution

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

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

Primary database model

Secondary database models

Spatial DBMS

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	42.91
Rank	#24	Overall
	#3	Search engines

Website

www.esgyn.cn

www.3ds.com/nuodb-distributed-sql-database

www.oracle.com/java/coherence

realm.io

solr.apache.org

Technical documentation

doc.nuodb.com

docs.oracle.com/en/middleware/standalone/coherence

realm.io/docs

solr.apache.org/resources.html

Developer

Esgyn

Dassault Systèmes

originally NuoDB, Inc.

Oracle

Realm, acquired by MongoDB in May 2019

Apache Software Foundation

Initial release

2015

2013

2007

2014

2006

Current release

14.1, August 2023

9.6.0, April 2024

License

Commercial or Open Source

commercial

limited edition free

commercial

Open Source

Apache Version 2

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++, Java

C++

Java

Server operating systems

Linux

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

All OS with a Java VM

Android
Backend: server-less
iOS
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

yes

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

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

All search fields are automatically indexed

SQL

Support of SQL

yes

Solr Parallel SQL Interface

APIs and other access methods

ADO.NET
JDBC
ODBC

JCache
JPA
RESTful HTTP API

Java API
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

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

.Net
C++
Java

.Net
Java

with Android only
Objective-C
React Native
Swift

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

Server-side scripts

Stored procedures

Java Stored Procedures

Java, SQL

runs within the applications so server-side scripts are unnecessary

Java plugins

Triggers

yes

Live Events

yes

Change Listeners

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

data is dynamically stored/cached on the nodes where it is read/written

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

yes

Managed transparently by NuoDB

yes, with selectable consistency level

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

tunable commit protocol

configurable

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

Durability

Support for making data persistent

yes

optionally

yes

In-memory capabilities

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

yes

Temporary table

yes

In-Memory realm

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Standard SQL roles/ privileges, Administrative Users

authentification to access the cache via certificates or http basic authentication

yes

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