DBMS > etcd vs. IBM Db2 warehouse vs. Oracle Coherence

System Properties Comparison etcd vs. IBM Db2 warehouse vs. Oracle Coherence

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Editorial information provided by DB-Engines

Name

Description

A distributed reliable key-value store

Cloud-based data warehousing service

Oracles in-memory data grid solution

Primary database model

Key-value store

Relational DBMS

Key-value store

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

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

Score	1.30
Rank	#164	Overall
	#75	Relational DBMS

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Website

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

www.ibm.com/products/db2/warehouse

www.oracle.com/java/coherence

Technical documentation

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

docs.oracle.com/en/middleware/standalone/coherence

Developer

IBM

Oracle

Initial release

2014

2007

Current release

3.4, August 2019

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

FreeBSD
Linux
Windows

experimental

hosted

All OS with a Java VM

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.

Import/export of XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

gRPC
JSON over HTTP

.NET Client API
JDBC
ODBC
OLE DB

JCache
JPA
RESTful HTTP API

Supported programming languages

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

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

.Net
C++
Java

Server-side scripts

Stored procedures

PL/SQL, SQL PL

Triggers

yes, watching key changes

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

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

authentification to access the cache via certificates or http basic authentication

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