DBMS > Citus vs. Google BigQuery vs. Kdb vs. Tibero

System Properties Comparison Citus vs. Google BigQuery vs. Kdb vs. Tibero

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

Large scale data warehouse service with append-only tables

High performance Time Series DBMS

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Relational DBMS

Time Series DBMS
Vector DBMS

Relational DBMS

Secondary database models

Document store

Relational DBMS

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

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

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

Score	1.78
Rank	#140	Overall
	#64	Relational DBMS

Website

www.citusdata.com

cloud.google.com/bigquery

kx.com

us.tmaxsoft.com/products/tibero

Technical documentation

docs.citusdata.com

cloud.google.com/bigquery/docs

code.kx.com

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

Google

Kx Systems, a division of First Derivatives plc

TmaxSoft

Initial release

2010

2000

kdb was released 2000, kdb+ in 2003

2003

Current release

8.1, December 2018

3.6, May 2018

6, April 2015

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

commercial

free 32-bit version

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 Assembler

Server operating systems

Linux

hosted

Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

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

specific XML type available, but no XML query functionality

yes

Secondary indexes

yes

table attribute 'grouped'

yes

SQL

Support of SQL

yes

standard, with numerous extensions

yes

SQL-like query language (q)

yes

APIs and other access methods

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

RESTful HTTP/JSON API

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

user defined functions

in JavaScript

user defined functions

Persistent Stored Procedure (PSM)

Triggers

yes

with views

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

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

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

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

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

planned for next version

User concepts

Access control

fine grained access rights according to SQL-standard

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

rights management via user accounts

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
» more

Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more

Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
» more

Key customers

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

Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
» more

Licensing and pricing models

upon request
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.