DBMS > BigObject vs. H2 vs. TerarkDB vs. TerminusDB

System Properties Comparison BigObject vs. H2 vs. TerarkDB vs. TerminusDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Key-value store

Graph DBMS

Secondary database models

Spatial DBMS

Document store
RDF store

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

Score	0.13
Rank	#329	Overall
	#147	Relational DBMS

Score	7.57
Rank	#47	Overall
	#30	Relational DBMS

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Score	0.19
Rank	#311	Overall
	#27	Graph DBMS

Website

bigobject.io

www.h2database.com

github.com/bytedance/terarkdb

terminusdb.com

Technical documentation

docs.bigobject.io

www.h2database.com/html/main.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

terminusdb.github.io/terminusdb/#

Developer

BigObject, Inc.

Thomas Mueller

ByteDance, originally Terark

DataChemist Ltd.

Initial release

2015

2005

2016

2018

Current release

2.2.220, July 2023

11.0.0, January 2023

License

Commercial or Open Source

commercial

free community edition available

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

restricted open source version available

Open Source

GPL V3

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++

Prolog, Rust

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

All OS with a Java VM

Linux

Data scheme

yes

schema-free

yes

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-like query language (WOQL)

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

JDBC
ODBC

C++ API
Java API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

Java

C++
Java

JavaScript
Python

Server-side scripts

Stored procedures

Lua

Java Stored Procedures and User-Defined Functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

With clustering: 2 database servers on different computers operate on identical copies of a database

none

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

in-memory journaling

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

Role-based access control

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