DBMS > Cubrid vs. IBM Db2 Event Store vs. Prometheus vs. Splunk

System Properties Comparison Cubrid vs. IBM Db2 Event Store vs. Prometheus vs. Splunk

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Editorial information provided by DB-Engines

Name

Description

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

Distributed Event Store optimized for Internet of Things use cases

Open-source Time Series DBMS and monitoring system

Analytics Platform for Big Data

Primary database model

Relational DBMS

Event Store
Time Series DBMS

Time Series DBMS

Search engine

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

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

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

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Score	86.45
Rank	#14	Overall
	#2	Search engines

Website

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

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

prometheus.io

www.splunk.com

Technical documentation

cubrid.org/manuals

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

prometheus.io/docs

docs.splunk.com/Documentation/Splunk

Developer

CUBRID Corporation, CUBRID Foundation

IBM

Splunk Inc.

Initial release

2008

2017

2015

2003

Current release

11.0, January 2021

2.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free developer edition available

Open Source

Apache 2.0

commercial

Limited free edition and free developer edition available

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

C, C++, Java

C and C++

Server operating systems

Linux
Windows

Linux

Linux, macOS, Windows for the developer addition

Linux
Windows

Linux
OS X
Solaris
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Import of XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

Splunk Search Processing Language for search commands

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

RESTful HTTP/JSON API

HTTP REST

Supported programming languages

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

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

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

Java 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

Source-replica replication

Active-active shard replication

yes

by Federation

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

none

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

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

fine grained access rights according to SQL-standard

Access rights for users and roles

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