DBMS > EsgynDB vs. ITTIA vs. Oracle Rdb

System Properties Comparison EsgynDB vs. ITTIA vs. Oracle Rdb

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Editorial information provided by DB-Engines

Name

Description

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

Edge Time Series DBMS with Real-Time Stream Processing

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.15
Rank	#332	Overall
	#144	Relational DBMS

Score	0.47
Rank	#253	Overall
	#21	Time Series DBMS

Score	0.93
Rank	#191	Overall
	#88	Relational DBMS

Website

www.esgyn.cn

www.ittia.com

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

Technical documentation

www.oracle.com/database/technologies/related/rdb-doc.html

Developer

Esgyn

ITTIA L.L.C.

Oracle, originally developed by Digital Equipment Corporation (DEC)

Initial release

2015

2007

1984

Current release

8.7

7.4.1.1, 2021

License

Commercial or Open Source

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++

Server operating systems

Linux

Linux
Windows

HP Open VMS

Data scheme

yes

Fixed schema

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

Typing

predefined data types such as float or date

yes

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

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

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
ODBC
RESTful HTTP API
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C
C++
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

yes

yes, on a single node

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

fine grained access rights according to SQL-standard

Database file passwords

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