DBMS > Ingres vs. JanusGraph vs. Lovefield vs. MarkLogic vs. MySQL

System Properties Comparison Ingres vs. JanusGraph vs. Lovefield vs. MarkLogic vs. MySQL

Editorial information provided by DB-Engines

Name

Description

Well established RDBMS

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Embeddable relational database for web apps written in pure JavaScript

Operational and transactional Enterprise NoSQL database

Widely used open source RDBMS

Primary database model

Relational DBMS

Graph DBMS

Relational DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store
Spatial DBMS

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

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	5.92
Rank	#58	Overall
	#10	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#6	Search engines

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

www.actian.com/databases/ingres

janusgraph.org

google.github.io/lovefield

www.marklogic.com

www.mysql.com

Technical documentation

docs.actian.com/ingres

docs.janusgraph.org

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

docs.marklogic.com

dev.mysql.com/doc

Developer

Actian Corporation

Linux Foundation; originally developed as Titan by Aurelius

Google

MarkLogic Corp.

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

1974

originally developed at University Berkely in early 1970s

2017

2014

2001

1995

Current release

11.2, May 2022

0.6.3, February 2023

2.1.12, February 2017

11.0, December 2022

8.4.0, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

GPL version 2. Commercial licenses with extended functionallity are 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.

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Implementation language

Java

JavaScript

C++

C and C++

Server operating systems

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux
OS X
Unix
Windows

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

tested with Chrome, Firefox, IE, Safari

Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

Schema can be enforced

yes

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.

but tools for importing/exporting data from/to XML-files available

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

yes

SQL92

yes

with proprietary extensions

APIs and other access methods

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Clojure
Java
Python

JavaScript

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

via XQuery or JavaScript

yes

proprietary syntax

Triggers

yes

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Ingres Star to access multiple databases simultaneously

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

none

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

Ingres Replicator

yes

none

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

can act as a resource manager in an XA/JTA transaction

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

yes, with Range Indexes

yes

User concepts

Access control

fine grained access rights according to SQL-standard

User authentification and security via Rexster Graph Server

Role-based access control at the document and subdocument levels

Users with fine-grained authorization concept

no user groups or roles

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