DBMS > BaseX vs. Cubrid vs. Google BigQuery vs. IBM Db2 Event Store vs. RRDtool

System Properties Comparison BaseX vs. Cubrid vs. Google BigQuery vs. IBM Db2 Event Store vs. RRDtool

Editorial information provided by DB-Engines

Name

Description

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

Large scale data warehouse service with append-only tables

Distributed Event Store optimized for Internet of Things use cases

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Primary database model

Native XML DBMS

Relational DBMS

Event Store
Time Series DBMS

Time Series DBMS

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

Score	1.73
Rank	#142	Overall
	#4	Native XML DBMS

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Website

basex.org

cubrid.com (korean)
cubrid.org (english)

cloud.google.com/bigquery

www.ibm.com/products/db2-event-store

oss.oetiker.ch/rrdtool

Technical documentation

docs.basex.org

cubrid.org/manuals

cloud.google.com/bigquery/docs

www.ibm.com/docs/en/db2-event-store

oss.oetiker.ch/rrdtool/doc

Developer

BaseX GmbH

CUBRID Corporation, CUBRID Foundation

Google

IBM

Tobias Oetiker

Initial release

2007

2008

2010

2017

1999

Current release

10.7, August 2023

11.0, January 2021

2.0

1.8.0, 2022

License

Commercial or Open Source

Open Source

BSD license

Open Source

Apache Version 2.0

commercial

free developer edition available

Open Source

GPL V2 and FLOSS

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

Java

C, C++, Java

C and C++

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

Linux
OS X
Windows

Linux
Windows

hosted

Linux

Linux, macOS, Windows for the developer addition

HP-UX
Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

XQuery supports types

yes

Numeric data only

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.

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

ADO.NET
JDBC
ODBC
OLE DB

RESTful HTTP/JSON API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

in-process shared library
Pipes

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Server-side scripts

Stored procedures

yes

Java Stored Procedures

user defined functions

in JavaScript

yes

Triggers

yes

via events

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

Active-active shard replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

multiple readers, single writer

ACID

Since BigQuery is designed for querying data

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

by using the rrdcached daemon

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes

In-memory capabilities

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

yes

User concepts

Access control

Users with fine-grained authorization concept on 4 levels

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)

fine grained access rights according to SQL-standard

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