DBMS > HEAVY.AI vs. Lovefield vs. MonetDB vs. Oracle vs. Oracle Coherence

System Properties Comparison HEAVY.AI vs. Lovefield vs. MonetDB vs. Oracle vs. Oracle Coherence

Editorial information provided by DB-Engines

Name

Description

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Embeddable relational database for web apps written in pure JavaScript

A relational database management system that stores data in columns

Widely used RDBMS

Oracles in-memory data grid solution

Primary database model

Relational DBMS

Key-value store

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

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

Website

github.com/heavyai/heavydb
www.heavy.ai

google.github.io/lovefield

www.monetdb.org

www.oracle.com/database

www.oracle.com/java/coherence

Technical documentation

docs.heavy.ai

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

www.monetdb.org/Documentation

docs.oracle.com/en/database

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

Developer

HEAVY.AI, Inc.

Google

MonetDB BV

Oracle

Initial release

2016

2014

2004

1980

2007

Current release

5.10, January 2022

2.1.12, February 2017

Dec2023 (11.49), December 2023

23c, September 2023

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 2.0

Open Source

Mozilla Public License 2.0

commercial

restricted free version is available

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

C++ and CUDA

JavaScript

C and C++

Java

Server operating systems

Linux

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

tested with Chrome, Firefox, IE, Safari

FreeBSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

All OS with a Java VM

Data scheme

yes

Schemaless in JSON and XML columns

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

yes

SQL 2003 with some extensions

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC
Thrift
Vega

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

JCache
JPA
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

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

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

.Net
C++
Java

Server-side scripts

Stored procedures

yes, in SQL, C, R

PL/SQL

also stored procedures in Java possible

Triggers

Using read-only observers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

none

Sharding via remote tables

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

Source-replica replication available in experimental status

Multi-source replication
Source-replica replication

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

isolation level can be parameterized

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

Version 12c introduced the new option 'Oracle Database In-Memory'

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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