DBMS > atoti vs. Lovefield vs. MonetDB vs. Oracle Coherence

System Properties Comparison atoti vs. Lovefield vs. MonetDB vs. Oracle Coherence

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Editorial information provided by DB-Engines

Name

Description

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

Embeddable relational database for web apps written in pure JavaScript

A relational database management system that stores data in columns

Oracles in-memory data grid solution

Primary database model

Object oriented DBMS

Relational DBMS

Key-value store

Secondary database models

Document store
Spatial DBMS

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

Score	0.45
Rank	#253	Overall
	#13	Object oriented DBMS

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Score	1.72
Rank	#135	Overall
	#62	Relational DBMS

Score	1.90
Rank	#127	Overall
	#21	Key-value stores

Website

atoti.io

google.github.io/lovefield

www.monetdb.org

www.oracle.com/java/coherence

Technical documentation

docs.atoti.io

github.com/google/lovefield/blob/master/docs/spec_index.md

www.monetdb.org/Documentation

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

Developer

ActiveViam

Google

MonetDB BV

Oracle

Initial release

2014

2004

2007

Current release

2.1.12, February 2017

Dec2023 (11.49), December 2023

14.1, August 2023

License

Commercial or Open Source

commercial

free versions available

Open Source

Apache 2.0

Open Source

Mozilla Public License 2.0

commercial

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

Java

JavaScript

Java

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

FreeBSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

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

SQL

Support of SQL

Multidimensional Expressions (MDX)

SQL-like query language

via JavaScript builder pattern

yes

SQL 2003 with some extensions

APIs and other access methods

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

JCache
JPA
RESTful HTTP API

Supported programming languages

JavaScript

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

.Net
C++
Java

Server-side scripts

Stored procedures

Python

yes, in SQL, C, R

Triggers

Using read-only observers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

none

Sharding via remote tables

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication available in experimental status

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

optionally

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

fine grained access rights according to SQL-standard

authentification to access the cache via certificates or http basic authentication

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