DBMS > ObjectBox vs. OushuDB vs. Splice Machine vs. TigerGraph

System Properties Comparison ObjectBox vs. OushuDB vs. Splice Machine vs. TigerGraph

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Editorial information provided by DB-Engines

Name

Description

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

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

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

Primary database model

Object oriented DBMS
Vector DBMS

Relational DBMS

Graph DBMS

Secondary database models

Time Series DBMS

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

Score	1.08
Rank	#179	Overall
	#6	Object oriented DBMS
	#9	Vector DBMS

Score	0.05
Rank	#357	Overall
	#151	Relational DBMS

Score	0.54
Rank	#244	Overall
	#114	Relational DBMS

Score	1.44
Rank	#152	Overall
	#14	Graph DBMS

Website

github.com/objectbox
objectbox.io

www.oushu.com/product/oushuDB

splicemachine.com

www.tigergraph.com

Technical documentation

docs.objectbox.io

www.oushu.com/documentation

splicemachine.com/how-it-works

docs.tigergraph.com

Developer

ObjectBox Limited

Oushu

Splice Machine

Initial release

2017

2014

2017

Current release

4.0 (May 2024)

4.0.1, August 2020

3.1, March 2021

License

Commercial or Open Source

Bindings are released under Apache 2.0

Apache License 2.0

commercial

Open Source

AGPL 3.0, commercial license available

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 and C++

Java

C++

Server operating systems

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Linux

Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

Full-featured ANSI SQL support

yes

SQL-like query language (GSQL)

APIs and other access methods

Proprietary native API

JDBC
ODBC

JDBC
Native Spark Datasource
ODBC

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

Supported programming languages

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

C
C++

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

C++
Java

Server-side scripts

Stored procedures

yes

Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Yes, via Full Spark Integration

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

yes

Kerberos, SSL and role based access

Access rights for users, groups and roles according to SQL-standard

Role-based access control

More information provided by the system vendor

News

MongoDB Realm & Device Sync alternatives – ObjectBox
17 September 2024

Local AI – what it is and why we need it
11 September 2024

First on-device Vector Database (aka Semantic Index) for iOS
24 July 2024

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

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