DBMS > EsgynDB vs. IRONdb vs. SQLite vs. TerminusDB vs. TimesTen

System Properties Comparison EsgynDB vs. IRONdb vs. SQLite vs. TerminusDB vs. TimesTen

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Widely used embeddable, in-process RDBMS

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

In-Memory RDBMS compatible to Oracle

Primary database model

Secondary database models

Document store
RDF store

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

www.esgyn.cn

www.circonus.com/solutions/time-series-database/

www.sqlite.org

terminusdb.com

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

Technical documentation

docs.circonus.com/irondb/category/getting-started

www.sqlite.org/docs.html

terminusdb.github.io/terminusdb/#

docs.oracle.com/database/timesten-18.1

Developer

Esgyn

Circonus LLC.

Dwayne Richard Hipp

DataChemist Ltd.

Oracle, TimesTen Performance Software, HP

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

Initial release

2015

2017

2000

2018

1998

Current release

V0.10.20, January 2018

3.45.3 (15 April 2024), April 2024

11.0.0, January 2023

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

Public Domain

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

C++, Java

C and C++

Prolog, Rust

Server operating systems

Linux

server-less

Linux

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

Data scheme

yes

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

yes

not rigid because of 'dynamic typing' concept.

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

yes

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

SQL-92 is not fully supported

SQL-like query language (WOQL)

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

JavaScript
Python

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

Java Stored Procedures

yes, in Lua

yes

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic, metric affinity per node

none

Graph Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

configurable replication factor, datacenter aware

none

Journaling Streams

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency or Eventual Consistency depending on configuration

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

via file-system locks

yes

Durability

Support for making data persistent

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

fine grained access rights according to SQL-standard

Role-based access control

fine grained access rights according to SQL-standard

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