DBMS > etcd vs. IBM Db2 vs. jBASE vs. MonetDB vs. RocksDB

System Properties Comparison etcd vs. IBM Db2 vs. jBASE vs. MonetDB vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

A distributed reliable key-value store

Common in IBM host environments, 2 different versions for host and Windows/Linux

A robust multi-value DBMS comprising development tools and middleware

A relational database management system that stores data in columns

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Key-value store

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Multivalue DBMS

Relational DBMS

Key-value store

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

Document store
Spatial DBMS

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

Score	7.03
Rank	#54	Overall
	#5	Key-value stores

Score	125.90
Rank	#9	Overall
	#6	Relational DBMS

Score	1.49
Rank	#156	Overall
	#3	Multivalue DBMS

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

etcd.io
github.com/etcd-io/etcd

www.ibm.com/products/db2

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

www.monetdb.org

rocksdb.org

Technical documentation

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

www.ibm.com/docs/en/db2

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

www.monetdb.org/Documentation

github.com/facebook/rocksdb/wiki

Developer

IBM

Rocket Software (formerly Zumasys)

MonetDB BV

Facebook, Inc.

Initial release

1983

host version

1991

2004

2013

Current release

3.4, August 2019

12.1, October 2016

5.7

Dec2023 (11.49), December 2023

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free version is available

commercial

Open Source

Mozilla Public License 2.0

Open Source

BSD

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 and C++

C++

Server operating systems

FreeBSD
Linux
Windows

experimental

AIX
HP-UX
Linux
Solaris
Windows
z/OS

AIX
Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

schema-free

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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

Secondary indexes

yes

SQL

Support of SQL

yes

Embedded SQL for jBASE in BASIC

yes

SQL 2003 with some extensions

APIs and other access methods

gRPC
JSON over HTTP

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

C++ API
Java API

Supported programming languages

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

.Net
Basic
Jabbascript
Java

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

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

yes, in SQL, C, R

Triggers

yes, watching key changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

only with Windows/Unix/Linux Version

Sharding

Sharding via remote tables

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

yes

with separate tools (MQ, InfoSphere)

yes

none

Source-replica replication available in experimental status

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

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

yes

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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