DBMS > EsgynDB vs. ITTIA vs. Kinetica vs. Trafodion vs. Yanza

System Properties Comparison EsgynDB vs. ITTIA vs. Kinetica vs. Trafodion vs. Yanza

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

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

Description

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

Edge Time Series DBMS with Real-Time Stream Processing

Fully vectorized database across both GPUs and CPUs

Transactional SQL-on-Hadoop DBMS

Time Series DBMS for IoT Applications

Primary database model

Secondary database models

Relational DBMS

Spatial DBMS
Time Series DBMS

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

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.44
Rank	#267	Overall
	#23	Time Series DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Website

yanza.com

Technical documentation

docs.kinetica.com

trafodion.apache.org/documentation.html

Developer

Esgyn

ITTIA L.L.C.

Kinetica

Apache Software Foundation, originally developed by HP

Yanza

Initial release

2015

2007

2012

2014

2015

Current release

8.7

7.1, August 2021

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

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++

C, C++

C++, Java

Server operating systems

Linux

Linux
Windows

Linux

Windows

Data scheme

yes

Fixed schema

yes

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

SQL-like DML and DDL statements

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
ODBC
RESTful HTTP API
WebSocket

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

HTTP API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C
C++
JavaScript (Node.js)
Python

C++
Java
JavaScript (Node.js)
Python

All languages supporting JDBC/ODBC/ADO.Net

any language that supports HTTP calls

Server-side scripts

Stored procedures

Java Stored Procedures

yes

user defined functions

Java Stored Procedures

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

yes

Source-replica replication

yes, via HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

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

GPU vRAM or System RAM

User concepts

Access control

fine grained access rights according to SQL-standard

Database file passwords

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

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