DBMS > Amazon Redshift vs. GBase vs. InfinityDB vs. Netezza vs. TimesTen

System Properties Comparison Amazon Redshift vs. GBase vs. InfinityDB vs. Netezza vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

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

Data warehouse and analytics appliance part of IBM PureSystems

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

Primary database model

Relational DBMS

Key-value store

Relational DBMS

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	1.11
Rank	#173	Overall
	#78	Relational DBMS

Score	0.00
Rank	#383	Overall
	#59	Key-value stores

Score	7.56
Rank	#48	Overall
	#31	Relational DBMS

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Website

aws.amazon.com/redshift

www.gbase.cn

boilerbay.com

www.ibm.com/products/netezza

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

Technical documentation

docs.aws.amazon.com/redshift

boilerbay.com/infinitydb/manual

docs.oracle.com/en/database/other-databases/timesten/index.html

Developer

Amazon (based on PostgreSQL)

General Data Technology Co., Ltd.

Boiler Bay Inc.

IBM

Oracle

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

Initial release

2012

2004

2002

2000

1998

Current release

GBase 8a, GBase 8s, GBase 8c

4.0

Release 22.1

License

Commercial or Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, Java, Python

Java

Server operating systems

hosted

Linux

All OS with a Java VM

Linux

included in appliance

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

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.

yes

Secondary indexes

restricted

yes

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

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

Standard with numerous extensions

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
C API
JDBC
ODBC

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

JDBC
ODBC
OLE DB

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

Supported programming languages

All languages supporting JDBC/ODBC

Java

C
C++
Fortran
Java
Lua
Perl
Python
R

C
C++
Java
Node.js
PL/SQL
Python

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

yes

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by range, list and hash) and vertical partitioning

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication

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

READ-COMMITTED or SERIALIZED

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

yes

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

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