DBMS > Infobright vs. STSdb vs. TerminusDB vs. Tigris

System Properties Comparison Infobright vs. STSdb vs. TerminusDB vs. Tigris

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Editorial information provided by DB-Engines

Name

Description

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

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

A horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure

Primary database model

Relational DBMS

Key-value store

Graph DBMS

Document store
Key-value store
Search engine
Time Series DBMS

Secondary database models

Document store
RDF store

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

Score	0.88
Rank	#198	Overall
	#92	Relational DBMS

Score	0.03
Rank	#365	Overall
	#54	Key-value stores

Score	0.19
Rank	#311	Overall
	#27	Graph DBMS

Score	0.05
Rank	#359	Overall
	#50	Document stores
	#52	Key-value stores
	#23	Search engines
	#37	Time Series DBMS

Website

ignitetech.com/softwarelibrary/infobrightdb

github.com/STSSoft/STSdb4

terminusdb.com

www.tigrisdata.com

Technical documentation

terminusdb.github.io/terminusdb/#

www.tigrisdata.com/docs

Developer

Ignite Technologies Inc.; formerly InfoBright Inc.

STS Soft SC

DataChemist Ltd.

Tigris Data, Inc.

Initial release

2005

2011

2018

2022

Current release

4.0.8, September 2015

11.0.0, January 2023

License

Commercial or Open Source

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

GPLv2, commercial license available

Open Source

GPL V3

Open Source

Apache Version 2.0

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

Prolog, Rust

Server operating systems

Linux
Windows

Windows

Linux

Linux
macOS
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

SQL-like query language (WOQL)

APIs and other access methods

ADO.NET
JDBC
ODBC

.NET Client API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

CLI Client
gRPC
RESTful HTTP API

Supported programming languages

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C#
Java

JavaScript
Python

Go
Java
JavaScript (Node.js)

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Graph Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Journaling Streams

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory journaling

yes, using FoundationDB

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

exploiting MySQL or PostgreSQL frontend capabilities

Role-based access control

Access rights for users and roles

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