DBMS > etcd vs. Graph Engine vs. OpenEdge vs. Oracle Rdb

System Properties Comparison etcd vs. Graph Engine vs. OpenEdge vs. Oracle Rdb

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Editorial information provided by DB-Engines

Name

Description

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Application development environment with integrated database management system

Primary database model

Key-value store

Graph DBMS
Key-value store

Relational DBMS

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

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

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	3.51
Rank	#86	Overall
	#46	Relational DBMS

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Website

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

www.graphengine.io

www.progress.com/openedge

www.oracle.com/database/technologies/related/rdb.html

Technical documentation

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

www.graphengine.io/docs/manual

documentation.progress.com/output/ua/OpenEdge_latest

www.oracle.com/database/technologies/related/rdb-doc.html

Developer

Microsoft

Progress Software Corporation

Oracle, originally developed by Digital Equipment Corporation (DEC)

Initial release

2010

1984

Current release

3.4, August 2019

OpenEdge 12.2, March 2020

7.4.1.1, 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

MIT License

commercial

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

.NET and C

Server operating systems

FreeBSD
Linux
Windows

experimental

.NET

AIX
HP-UX
Linux
Solaris
Windows

HP Open VMS

Data scheme

schema-free

yes

Flexible Schema (defined schema, partial schema, 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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

yes

APIs and other access methods

gRPC
JSON over HTTP

RESTful HTTP API

JDBC
ODBC

Supported programming languages

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

C#
C++
F#
Visual Basic

Progress proprietary ABL (Advanced Business Language)

Server-side scripts

Stored procedures

yes

Triggers

yes, watching key changes

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

since Version 11.4

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication

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, on a single node

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent 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

Users and groups

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