DBMS > HEAVY.AI vs. Kinetica vs. Oracle vs. OrientDB vs. Realm

System Properties Comparison HEAVY.AI vs. Kinetica vs. Oracle vs. OrientDB vs. Realm

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

Fully vectorized database across both GPUs and CPUs

Widely used RDBMS

Multi-model DBMS (Document, Graph, Key/Value)

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

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store

Document store

Secondary database models

Spatial DBMS

Spatial DBMS
Time Series 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	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	7.60
Rank	#52	Overall
	#9	Document stores

Website

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

www.kinetica.com

www.oracle.com/database

orientdb.org

realm.io

Technical documentation

docs.heavy.ai

docs.kinetica.com

docs.oracle.com/en/database

www.orientdb.com/docs/last/index.html

realm.io/docs

Developer

HEAVY.AI, Inc.

Kinetica

Oracle

OrientDB LTD; CallidusCloud; SAP

Realm, acquired by MongoDB in May 2019

Initial release

2016

2012

1980

2010

2014

Current release

5.10, January 2022

7.1, August 2021

23c, September 2023

3.2.29, March 2024

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

commercial

restricted free version is available

Open Source

Apache version 2

Open Source

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

C, C++

C and C++

Java

Server operating systems

Linux

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

All OS with a Java JDK (>= JDK 6)

Android
Backend: server-less
iOS
Windows

Data scheme

yes

Schemaless in JSON and XML columns

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

with proprietary extensions

SQL-like query language, no joins

APIs and other access methods

JDBC
ODBC
Thrift
Vega

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

C++
Java
JavaScript (Node.js)
Python

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

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

user defined functions

PL/SQL

also stored procedures in Java possible

Java, Javascript

runs within the applications so server-side scripts are unnecessary

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Hooks

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

Sharding, horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

Multi-source replication
Source-replica replication

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

Transaction concepts

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

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

GPU vRAM or System RAM

yes

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

yes

In-Memory realm

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

Access rights for users and roles; record level security configurable

yes

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