DBMS > Hazelcast vs. HugeGraph vs. Kinetica vs. MySQL vs. UniData,UniVerse

System Properties Comparison Hazelcast vs. HugeGraph vs. Kinetica vs. MySQL vs. UniData,UniVerse

Editorial information provided by DB-Engines

Name

Description

A widely adopted in-memory data grid

A fast-speed and highly-scalable Graph DBMS

Fully vectorized database across both GPUs and CPUs

Widely used open source RDBMS

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Key-value store

Graph DBMS

Relational DBMS

Key/Value like access via memcached API

Multivalue DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

Spatial DBMS
Time Series DBMS

Document store
Spatial DBMS

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

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	3.16
Rank	#97	Overall
	#2	Multivalue DBMS

Website

hazelcast.com

github.com/hugegraph
hugegraph.apache.org

www.kinetica.com

www.mysql.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

hazelcast.org/imdg/docs

hugegraph.apache.org/docs

docs.kinetica.com

dev.mysql.com/doc

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Hazelcast

Baidu

Kinetica

Oracle

since 2010, originally MySQL AB, then Sun

Rocket Software

Initial release

2008

2018

2012

1995

1985

Current release

5.3.6, November 2023

0.9

7.1, August 2021

8.4.0, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache Version 2.0

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are 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.

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

Java

C, C++

C and C++

Server operating systems

All OS with a Java VM

Linux
macOS
Unix

Linux

FreeBSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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

the object must implement a serialization strategy

yes

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements

yes

with proprietary extensions

yes

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

Groovy
Java
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

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

asynchronous Gremlin script jobs

user defined functions

yes

proprietary syntax

yes

Triggers

yes

Events

yes

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

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

yes

depending on used storage backend, e.g. Cassandra and HBase

Source-replica replication

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

not for MyISAM storage engine

Transaction concepts

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

one or two-phase-commit; repeatable reads; read commited

ACID

not for MyISAM storage engine

ACID

configurable

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 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

Role-based access control

Users, roles and permissions

Access rights for users and roles on table level

Users with fine-grained authorization concept

no user groups or roles

Access rights according to SQL-standard and operating system based

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.