DBMS > Fujitsu Enterprise Postgres vs. Kdb vs. Oracle vs. TempoIQ

System Properties Comparison Fujitsu Enterprise Postgres vs. Kdb vs. Oracle vs. TempoIQ

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Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.

High performance Time Series DBMS

Widely used RDBMS

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

Relational DBMS

Time Series DBMS
Vector DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

Relational DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	0.31
Rank	#285	Overall
	#129	Relational DBMS

Score	7.55
Rank	#53	Overall
	#3	Time Series DBMS
	#1	Vector DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Website

www.postgresql.fastware.com

kx.com

www.oracle.com/database

tempoiq.com (offline)

Technical documentation

www.postgresql.fastware.com/product-manuals

code.kx.com

docs.oracle.com/en/database

Developer

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

Kx Systems, a division of First Derivatives plc

Oracle

TempoIQ

Initial release

2000

kdb was released 2000, kdb+ in 2003

1980

2012

Current release

Fujitsu Enterprise Postgres 14, January 2022

3.6, May 2018

23c, September 2023

License

Commercial or Open Source

commercial

free 32-bit version

commercial

restricted free version is available

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 and C++

Server operating systems

Linux
Windows

Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Data scheme

yes

Schemaless in JSON and XML columns

schema-free

Typing

predefined data types such as float or date

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

yes

table attribute 'grouped'

yes

SQL

Support of SQL

yes

SQL-like query language (q)

yes

with proprietary extensions

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

HTTP API

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

PL/SQL

also stored procedures in Java possible

Triggers

yes

with views

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

partitioning by range, list and by hash

horizontal partitioning

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

similar paradigm used for internal processing

can be realized in PL/SQL

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

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

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

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

fine grained access rights according to SQL-standard

rights management via user accounts

fine grained access rights according to SQL-standard

simple authentication-based access control

More information provided by the system vendor

Specific characteristics

100% compatible with community PostgreSQL
» more

Integrated columnar database & programming system for streaming, real time and historical...
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Competitive advantages

Built-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
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provides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more

Typical application scenarios

Transactional payments applications, reporting and mixed workloads.
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tick database streaming sensor data massive intelligence applications oil and gas...
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Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more

Market metrics

Over 30 years experience in database technology. Over 20 years in Postgres development...
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kdb+ performance and reliability proven by our customers in critical infrastructure...
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Licensing and pricing models

Core based licensing
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upon request
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