DBMS > HugeGraph vs. Memcached vs. SQLite vs. Stardog vs. TigerGraph

System Properties Comparison HugeGraph vs. Memcached vs. SQLite vs. Stardog vs. TigerGraph

Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

In-memory key-value store, originally intended for caching

Widely used embeddable, in-process RDBMS

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

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

Primary database model

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

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	18.08
Rank	#32	Overall
	#4	Key-value stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

github.com/hugegraph
hugegraph.apache.org

Technical documentation

hugegraph.apache.org/docs

github.com/memcached/memcached/wiki

www.sqlite.org/docs.html

docs.stardog.com

docs.tigergraph.com

Developer

Baidu

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Dwayne Richard Hipp

Stardog-Union

Initial release

2018

2003

2000

2010

2017

Current release

0.9

1.6.27, May 2024

3.46.0 (23 May 2024), May 2024

7.3.0, May 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

BSD license

Open Source

Public Domain

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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.

Implementation language

Java

C++

Server operating systems

Linux
macOS
Unix

FreeBSD
Linux
OS X
Unix
Windows

server-less

Linux
macOS
Windows

Linux

Data scheme

yes

schema-free

yes

dynamic column types

schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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.

Import/export of XML data possible

Secondary indexes

yes

also supports composite index and range index

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

SQL-92 is not fully supported

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

SQL-like query language (GSQL)

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

Proprietary protocol

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

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

Supported programming languages

Groovy
Java
Python

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

C++
Java

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

user defined functions and aggregates, HTTP Server extensions in Java

yes

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

yes

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

none

Repcached, a Memcached patch, provides this functionallity

none

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

edges in graph

yes

relationships in graphs

yes

Relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

User concepts

Access control

Users, roles and permissions

yes

using SASL (Simple Authentication and Security Layer) protocol

Access rights for users and roles

Role-based access control

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