DBMS > BigchainDB vs. Faircom EDGE vs. Stardog vs. TerminusDB vs. TimesTen

System Properties Comparison BigchainDB vs. Faircom EDGE vs. Stardog vs. TerminusDB vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

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

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

In-Memory RDBMS compatible to Oracle

Primary database model

Document store

Key-value store
Relational DBMS

Graph DBMS
RDF store

Graph DBMS

Relational DBMS

Secondary database models

Document store
RDF store

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	0.02
Rank	#368	Overall
	#54	Key-value stores
	#156	Relational DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

www.bigchaindb.com

www.faircom.com/products/faircom-edge

www.stardog.com

terminusdb.com

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

bigchaindb.readthedocs.io/en/latest

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

docs.stardog.com

terminusdb.github.io/terminusdb/#

docs.oracle.com/database/timesten-18.1

Developer

FairCom Corporation

Stardog-Union

DataChemist Ltd.

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2016

1979

2010

2018

1998

Current release

V3, October 2020

7.3.0, May 2020

11.0.0, January 2023

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

AGPL v3

commercial

Restricted, free version available

commercial

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

Open Source

GPL V3

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

Python

ANSI C, C++

Java

Prolog, Rust

Server operating systems

Linux

Android
Linux

ARM, x86
Raspbian
Windows

Linux
macOS
Windows

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

yes, ANSI Standard SQL 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

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

yes

ANSI SQL queries

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

SQL-like query language (WOQL)

yes

APIs and other access methods

CLI Client
RESTful HTTP API

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

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

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

JavaScript
Python

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

user defined functions and aggregates, HTTP Server extensions in Java

yes

PL/SQL

Triggers

yes

via event handlers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

File partitioning

Customizable business rules for partitioning

none

Graph Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Synchronous and asynchronous realtime replication based on transaction logs

Multi-source replication in HA-Cluster

Journaling Streams

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

Immediate Consistency in HA-Cluster

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

when using SQL

yes

relationships in graphs

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

in-memory journaling

yes

by means of logfiles and checkpoints

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

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

Access rights for users and roles

Role-based access control

fine grained access rights according to SQL-standard

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