DBMS > Cubrid vs. KeyDB vs. Prometheus vs. Splunk

System Properties Comparison Cubrid vs. KeyDB vs. Prometheus vs. Splunk

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Open-source Time Series DBMS and monitoring system

Analytics Platform for Big Data

Primary database model

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

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	0.71
Rank	#226	Overall
	#33	Key-value stores

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)

github.com/Snapchat/KeyDB
keydb.dev

prometheus.io

www.splunk.com

Technical documentation

cubrid.org/manuals

docs.keydb.dev

prometheus.io/docs

docs.splunk.com/Documentation/Splunk

Developer

CUBRID Corporation, CUBRID Foundation

EQ Alpha Technology Ltd.

Splunk Inc.

Initial release

2008

2019

2015

2003

Current release

11.0, January 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

BSD-3

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++

Server operating systems

Linux
Windows

Linux

Linux
Windows

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

by using the Redis Search module

yes

SQL

Support of SQL

yes

Splunk Search Processing Language for search commands

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

Proprietary protocol

RESP - REdis Serialization Protoco

RESTful HTTP/JSON API

HTTP REST

Supported programming languages

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

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
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

Lua

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

Multi-source replication
Source-replica 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
Strong eventual consistency with CRDTs

none

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Optimistic locking, atomic execution of commands blocks and scripts

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

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

simple password-based access control and ACL

Access rights for users and roles

More information provided by the system vendor

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Enterprise Search Engines almost double their popularity in the last 12 months
2 July 2014, Paul Andlinger

show all

Recent citations in the news

Oh, snap! Snap snaps up database developer KeyDB
12 May 2022, TechCrunch

Snap Acquires KeyDB for Open-Source Services
17 May 2022, XR Today

Garnet–open-source faster cache-store speeds up applications, services
18 March 2024, microsoft.com

Dragonfly 1.0 Released For What Claims To Be The World's Fastest In-Memory Data Store
20 March 2023, Phoronix

Redis 6 arrives with multithreading for faster I/O
30 April 2020, InfoWorld

provided by Google News

VTEX scales to 150 million metrics using Amazon Managed Service for Prometheus | Amazon Web Services
10 March 2024, AWS Blog

VictoriaMetrics Offers Prometheus Replacement for Time Series Monitoring
17 July 2023, The New Stack

Linux System Monitoring with Prometheus, Grafana, and collectd
1 February 2024, Linux Journal

How to reduce Istio sidecar metric cardinality with Amazon Managed Service for Prometheus | Amazon Web Services
10 October 2023, AWS Blog

Consider Grafana vs. Prometheus for your time-series tools
18 October 2021, TechTarget

provided by Google News

Share this page