DBMS > Dgraph vs. HEAVY.AI vs. Kinetica vs. MySQL vs. TerminusDB

System Properties Comparison Dgraph vs. HEAVY.AI vs. Kinetica vs. MySQL vs. TerminusDB

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

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 open source RDBMS

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Graph DBMS

Relational DBMS

Key/Value like access via memcached API

Graph DBMS

Secondary database models

Spatial DBMS

Spatial DBMS
Time Series DBMS

Document store
Spatial DBMS

Document store
RDF store

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

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

dgraph.io

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

www.kinetica.com

www.mysql.com

terminusdb.com

Technical documentation

terminusdb.github.io/terminusdb/#

Developer

Dgraph Labs, Inc.

HEAVY.AI, Inc.

Kinetica

Oracle

since 2010, originally MySQL AB, then Sun

DataChemist Ltd.

Initial release

2016

2012

1995

2018

Current release

5.10, January 2022

7.1, August 2021

8.4.0, April 2024

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2; enterprise edition available

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

C++ and CUDA

C, C++

C and C++

Prolog, Rust

Server operating systems

Linux
OS X
Windows

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

schema-free

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 (WOQL)

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

JDBC
ODBC
Thrift
Vega

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

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

All languages supporting JDBC/ODBC/Thrift
Python

C++
Java
JavaScript (Node.js)
Python

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

JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

yes

proprietary syntax

yes

Triggers

yes

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

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

Round robin

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Multi-source replication

Source-replica replication

Multi-source replication
Source-replica replication

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

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

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

in-memory journaling

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

User concepts

Access control

Planned for future releases

fine grained access rights according to SQL-standard

Access rights for users and roles on table level

Users with fine-grained authorization concept

no user groups or roles

Role-based access control

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