DBMS > etcd vs. Hazelcast vs. IBM Db2

System Properties Comparison etcd vs. Hazelcast vs. IBM Db2

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Editorial information provided by DB-Engines

Name

Description

A distributed reliable key-value store

A widely adopted in-memory data grid

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

Primary database model

Key-value store

Relational DBMS

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

Secondary database models

Document store

JSON support with IMDG 3.12

Document store
RDF store

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

with Db2 Spatial Extender

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

Score	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	128.46
Rank	#8	Overall
	#5	Relational DBMS

Website

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

hazelcast.com

www.ibm.com/products/db2

Technical documentation

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

hazelcast.org/imdg/docs

www.ibm.com/docs/en/db2

Developer

Hazelcast

IBM

Initial release

2008

1983

host version

Current release

3.4, August 2019

5.3.6, November 2023

12.1, October 2016

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2; commercial licenses available

commercial

free version is 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

Java

C and C++

Server operating systems

FreeBSD
Linux
Windows

experimental

All OS with a Java VM

AIX
HP-UX
Linux
Solaris
Windows
z/OS

Data scheme

schema-free

yes

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.

yes

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

gRPC
JSON over HTTP

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

Supported programming languages

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

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

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

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

yes

Triggers

yes, watching key changes

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

only with Windows/Unix/Linux Version

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

Replicated Map

yes

with separate tools (MQ, InfoSphere)

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Foreign keys

Referential integrity

yes

Transaction concepts

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

one or two-phase-commit; repeatable reads; read commited

ACID

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

Role-based access control

fine grained access rights according to SQL-standard

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