DBMS > Citus vs. Hive vs. HugeGraph vs. MySQL vs. TinkerGraph

System Properties Comparison Citus vs. Hive vs. HugeGraph vs. MySQL vs. TinkerGraph

Editorial information provided by DB-Engines

Name

Description

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

data warehouse software for querying and managing large distributed datasets, built on Hadoop

A fast-speed and highly-scalable Graph DBMS

Widely used open source RDBMS

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Relational DBMS

Graph DBMS

Relational DBMS

Key/Value like access via memcached API

Graph DBMS

Secondary database models

Document store

Document store
Spatial DBMS

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Trend Chart

Score	2.15
Rank	#117	Overall
	#56	Relational DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	0.13
Rank	#345	Overall
	#35	Graph DBMS

Website

www.citusdata.com

hive.apache.org

github.com/hugegraph
hugegraph.apache.org

www.mysql.com

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

docs.citusdata.com

cwiki.apache.org/confluence/display/Hive/Home

hugegraph.apache.org/docs

dev.mysql.com/doc

Developer

Apache Software Foundation

initially developed by Facebook

Baidu

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2010

2012

2018

1995

2009

Current release

8.1, December 2018

3.1.3, April 2022

0.9

8.4.0, April 2024

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

Open Source

Apache Version 2

Open Source

Apache Version 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C and C++

Java

Server operating systems

Linux

All OS with a Java VM

Linux
macOS
Unix

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

yes

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

specific XML type available, but no XML query functionality

yes

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

yes

standard, with numerous extensions

SQL-like DML and DDL statements

yes

with proprietary extensions

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
ODBC
Thrift

Java API
RESTful HTTP API
TinkerPop Gremlin

ADO.NET
JDBC
ODBC
Proprietary native API

TinkerPop 3

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C++
Java
PHP
Python

Groovy
Java
Python

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

Groovy
Java

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

user defined functions and integration of map-reduce

asynchronous Gremlin script jobs

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

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

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

selectable replication factor

yes

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

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

none

Foreign keys

Referential integrity

yes

edges in graph

yes

not for MyISAM storage engine

yes

Relationships in graphs

Transaction concepts

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

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

optional

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

Users, roles and permissions

Users with fine-grained authorization concept

no user groups or roles

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