DBMS > GridGain vs. HugeGraph vs. SQL.JS vs. SQLite vs. TigerGraph

System Properties Comparison GridGain vs. HugeGraph vs. SQL.JS vs. SQLite vs. TigerGraph

Editorial information provided by DB-Engines

Name

Description

GridGain is an in-memory computing platform, built on Apache Ignite

A fast-speed and highly-scalable Graph DBMS

Port of SQLite to JavaScript

Widely used embeddable, in-process RDBMS

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

Primary database model

Key-value store
Relational DBMS

Graph DBMS

Relational DBMS

Graph DBMS

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

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	0.63
Rank	#241	Overall
	#112	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

www.gridgain.com

github.com/hugegraph
hugegraph.apache.org

sql.js.org

www.sqlite.org

www.tigergraph.com

Technical documentation

www.gridgain.com/docs/index.html

hugegraph.apache.org/docs

sql.js.org/documentation/index.html

www.sqlite.org/docs.html

docs.tigergraph.com

Developer

GridGain Systems, Inc.

Baidu

Alon Zakai

enhancements implemented by others

Dwayne Richard Hipp

Initial release

2007

2018

2012

2000

2017

Current release

GridGain 8.5.1

0.9

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Public Domain

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++, .Net

Java

JavaScript

C++

Server operating systems

Linux
OS X
Solaris
Windows

Linux
macOS
Unix

server-less, requires a JavaScript environment (browser, Node.js)

server-less

Linux

Data scheme

yes

dynamic column types

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.

yes

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

yes

SQL-92 is not fully supported

yes

SQL-92 is not fully supported

SQL-like query language (GSQL)

APIs and other access methods

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Java API
RESTful HTTP API
TinkerPop Gremlin

JavaScript API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

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

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

Groovy
Java
Python

JavaScript

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

C++
Java

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

asynchronous Gremlin script jobs

yes

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

via hugegraph-spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

none

Foreign keys

Referential integrity

yes

edges in graph

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

except by serializing a db to a file

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

Security Hooks for custom implementations

Users, roles and permissions

Role-based access control

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