DBMS > InfinityDB vs. LevelDB vs. Netezza vs. Transbase

System Properties Comparison InfinityDB vs. LevelDB vs. Netezza vs. Transbase

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Editorial information provided by DB-Engines

Name

Description

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

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Data warehouse and analytics appliance part of IBM PureSystems

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Key-value store

Relational DBMS

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

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

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

boilerbay.com

github.com/google/leveldb

www.ibm.com/products/netezza

www.transaction.de/en/products/transbase.html

Technical documentation

boilerbay.com/infinitydb/manual

github.com/google/leveldb/blob/main/doc/index.md

www.transaction.de/en/products/transbase/features.html

Developer

Boiler Bay Inc.

Google

IBM

Transaction Software GmbH

Initial release

2002

2011

2000

1987

Current release

4.0

1.23, February 2021

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

Open Source

BSD

commercial

free development license

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

Java

C++

C and C++

Server operating systems

All OS with a Java VM

Illumos
Linux
OS X
Windows

Linux

included in appliance

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

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

schema-free

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.

Secondary indexes

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

yes

SQL

Support of SQL

yes

APIs and other access methods

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

JDBC
ODBC
OLE DB

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Java

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C
C++
Fortran
Java
Lua
Perl
Python
R

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

READ-COMMITTED or SERIALIZED

Immediate Consistency

Foreign keys

Referential integrity

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

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

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

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