DBMS > Cachelot.io vs. Cubrid vs. IBM Db2 Event Store vs. Riak TS

System Properties Comparison Cachelot.io vs. Cubrid vs. IBM Db2 Event Store vs. Riak TS

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Editorial information provided by DB-Engines

Name

Description

In-memory caching system

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

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Key-value store

Relational DBMS

Event Store
Time Series DBMS

Time Series DBMS

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

Score	0.04
Rank	#388	Overall
	#62	Key-value stores

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Website

cachelot.io

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

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

Technical documentation

cubrid.org/manuals

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

www.tiot.jp/riak-docs/riak/ts/latest

Developer

CUBRID Corporation, CUBRID Foundation

IBM

Open Source, formerly Basho Technologies

Initial release

2015

2008

2017

2015

Current release

11.0, January 2021

2.0

3.0.0, September 2022

License

Commercial or Open Source

Open Source

Simplified BSD License

Open Source

Apache Version 2.0

commercial

free developer edition available

Open Source

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, C++, Java

C and C++

Erlang

Server operating systems

FreeBSD
Linux
OS X

Linux
Windows

Linux

Linux, macOS, Windows for the developer addition

Linux
OS X

Data scheme

schema-free

yes

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.

Secondary indexes

yes

restricted

SQL

Support of SQL

yes

through the embedded Spark runtime

yes, limited

APIs and other access methods

Memcached protocol

ADO.NET
JDBC
ODBC
OLE DB

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

HTTP API
Native Erlang Interface

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

Active-active shard replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

Transaction concepts

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

ACID

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

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