DBMS > Citus vs. Heroic vs. MySQL vs. TigerGraph vs. TinkerGraph

System Properties Comparison Citus vs. Heroic vs. MySQL vs. TigerGraph vs. TinkerGraph

Editorial information provided by DB-Engines

Name

Description

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Widely used open source RDBMS

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

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

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Graph DBMS

Secondary database models

Document store

Document store
Spatial DBMS

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

Score	2.15
Rank	#117	Overall
	#56	Relational DBMS

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Score	0.13
Rank	#345	Overall
	#35	Graph DBMS

Website

www.citusdata.com

github.com/spotify/heroic

www.mysql.com

www.tigergraph.com

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

Technical documentation

docs.citusdata.com

spotify.github.io/heroic

dev.mysql.com/doc

docs.tigergraph.com

Developer

Spotify

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2010

2014

1995

2017

2009

Current release

8.1, December 2018

8.4.0, April 2024

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

Open Source

Apache 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

C++

Java

Server operating systems

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

schema-free

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

via Elasticsearch

yes

SQL

Support of SQL

yes

standard, with numerous extensions

yes

with proprietary extensions

SQL-like query language (GSQL)

APIs and other access methods

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

HQL (Heroic Query Language, a JSON-based language)
HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

TinkerPop 3

Supported programming languages

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

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

C++
Java

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

proprietary syntax

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

yes

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

none

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Relationships in graphs

yes

Relationships in graphs

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

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

Users with fine-grained authorization concept

no user groups or roles

Role-based access control

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