DBMS > InfinityDB vs. Interbase vs. Kinetica vs. MySQL vs. Trafodion

System Properties Comparison InfinityDB vs. Interbase vs. Kinetica vs. MySQL vs. Trafodion

Editorial information provided by DB-Engines

Name

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

Description

A Java embedded Key-Value Store which extends the Java Map interface

Light-weight proven RDBMS

originally from Borland

Fully vectorized database across both GPUs and CPUs

Widely used open source RDBMS

Transactional SQL-on-Hadoop DBMS

Primary database model

Key-value store

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
Spatial DBMS

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

Score	0.00
Rank	#378	Overall
	#57	Key-value stores

Score	4.61
Rank	#72	Overall
	#39	Relational DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

boilerbay.com

www.embarcadero.com/products/interbase

www.kinetica.com

www.mysql.com

trafodion.apache.org

Technical documentation

boilerbay.com/infinitydb/manual

docs.embarcadero.com/products/interbase

docs.kinetica.com

dev.mysql.com/doc

trafodion.apache.org/documentation.html

Developer

Boiler Bay Inc.

Embarcadero

Kinetica

Oracle

since 2010, originally MySQL AB, then Sun

Apache Software Foundation, originally developed by HP

Initial release

2002

1984

2012

1995

2014

Current release

4.0

InterBase 2020, December 2019

7.1, August 2021

8.4.0, April 2024

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C, C++

C and C++

C++, Java

Server operating systems

All OS with a Java VM

Android
iOS
Linux
OS X
Windows

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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.

export as XML data possible

yes

Secondary indexes

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

with proprietary extensions

yes

APIs and other access methods

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

ADO.NET
JDBC
ODBC

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
JDBC
ODBC

Supported programming languages

Java

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

C++
Java
JavaScript (Node.js)
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

Interbase procedure and trigger language

user defined functions

yes

proprietary syntax

Java Stored Procedures

Triggers

yes

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

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Interbase Change Views

Source-replica replication

Multi-source replication
Source-replica replication

yes, via HBase

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

READ-COMMITTED or SERIALIZED

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

yes

table locks or row locks depending on storage engine

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles on table level

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

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