DBMS > gStore vs. ObjectBox vs. Postgres-XL vs. TigerGraph

System Properties Comparison gStore vs. ObjectBox vs. Postgres-XL vs. TigerGraph

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Editorial information provided by DB-Engines

Name

Description

A native Graph DBMS to store and maintain very large RDF datasets.

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

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

Primary database model

Graph DBMS
RDF store

Object oriented DBMS
Vector DBMS

Relational DBMS

Graph DBMS

Secondary database models

Time Series DBMS

Document store
Spatial DBMS

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

Score	0.14
Rank	#342	Overall
	#34	Graph DBMS
	#16	RDF stores

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS
	#7	Vector DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

en.gstore.cn

github.com/objectbox
objectbox.io

www.postgres-xl.org

www.tigergraph.com

Technical documentation

en.gstore.cn/#/enDocs

docs.objectbox.io

www.postgres-xl.org/documentation

docs.tigergraph.com

Developer

ObjectBox Limited

Initial release

2016

2017

2014

since 2012, originally named StormDB

2017

Current release

1.2, November 2023

4.0 (May 2024)

10 R1, October 2018

License

Commercial or Open Source

Open Source

BSD

Bindings are released under Apache 2.0

Apache License 2.0

Open Source

Mozilla public license

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

C++

C and C++

C++

Server operating systems

Linux

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Linux
macOS

Linux

Data scheme

schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

yes

yes, plus "flex" map-like types

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

SQL-like query language (GSQL)

APIs and other access methods

HTTP API
SPARQL 1.1

Proprietary native API

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

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

Supported programming languages

C++
Java
JavaScript (Node.js)
PHP
Python

C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift

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

C++
Java

Server-side scripts

Stored procedures

yes

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Data sync between devices allowing occasional connected databases to work completely offline

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

yes

ACID

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

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.

User concepts

Access control

Users, roles and permissions, Role-Based Access Control (RBAC) supported

yes

fine grained access rights according to SQL-standard

Role-based access control

More information provided by the system vendor

News

Retrieval Augmented Generation (RAG) with vector databases: Expanding AI Capabilities
18 June 2024

The on-device Vector Database for Android and Java
29 May 2024

Vector search: making sense of search queries
29 May 2024

Python on-device Vector and Object Database for Local AI
28 May 2024

Evolution of search: traditional vs vector search
23 May 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

Recent citations in the news

ObjectBox Raises $2M in Funding
4 December 2018, FinSMEs

The Megashift Towards Decentralized Edge Computing
27 August 2021, hackernoon.com

provided by Google News

TigerGraph Unveils CoPilot, Version 4.0, and New CEO
30 April 2024, Datanami

How TigerGraph CoPilot enables graph-augmented AI
30 April 2024, InfoWorld

TigerGraph unveils GenAI assistant, introduces new CEO
30 April 2024, TechTarget

TigerGraph Bolsters DB for Enterprise Graph Workloads
1 November 2023, Datanami

TigerGraph update adds enterprise-scale capabilities
31 October 2023, TechTarget

provided by Google News

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