DBMS > Lovefield vs. Microsoft Azure Cosmos DB vs. MonetDB vs. Trafodion

System Properties Comparison Lovefield vs. Microsoft Azure Cosmos DB vs. MonetDB vs. Trafodion

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Embeddable relational database for web apps written in pure JavaScript

Globally distributed, horizontally scalable, multi-model database service

A relational database management system that stores data in columns

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Website

google.github.io/lovefield

azure.microsoft.com/services/cosmos-db

www.monetdb.org

trafodion.apache.org

Technical documentation

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

learn.microsoft.com/azure/cosmos-db

www.monetdb.org/Documentation

trafodion.apache.org/documentation.html

Developer

Google

Microsoft

MonetDB BV

Apache Software Foundation, originally developed by HP

Initial release

2014

2004

2014

Current release

2.1.12, February 2017

Dec2023 (11.49), December 2023

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Mozilla Public License 2.0

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

JavaScript

C++, Java

Server operating systems

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

tested with Chrome, Firefox, IE, Safari

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

SQL-like query language

yes

SQL 2003 with some extensions

yes

APIs and other access methods

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

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

ADO.NET
JDBC
ODBC

Supported programming languages

JavaScript

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

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

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

JavaScript

yes, in SQL, C, R

Java Stored Procedures

Triggers

Using read-only observers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding via remote tables

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Implicit feature of the cloud service

none

Source-replica replication available in experimental status

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

yes

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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