DBMS > Amazon Neptune vs. Geode vs. OpenEdge vs. Realm vs. SQLite

System Properties Comparison Amazon Neptune vs. Geode vs. OpenEdge vs. Realm vs. SQLite

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

Application development environment with integrated database management system

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Widely used embeddable, in-process RDBMS

Primary database model

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

Score	2.20
Rank	#119	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	3.51
Rank	#86	Overall
	#46	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

aws.amazon.com/neptune

geode.apache.org

www.progress.com/openedge

realm.io

www.sqlite.org

Technical documentation

aws.amazon.com/neptune/developer-resources

geode.apache.org/docs

documentation.progress.com/output/ua/OpenEdge_latest

realm.io/docs

www.sqlite.org/docs.html

Developer

Amazon

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Progress Software Corporation

Realm, acquired by MongoDB in May 2019

Dwayne Richard Hipp

Initial release

2017

2002

1984

2014

2000

Current release

1.1, February 2017

OpenEdge 12.2, March 2020

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

hosted

All OS with a Java VM

the JDK (8 or later) is also required

AIX
HP-UX
Linux
Solaris
Windows

Android
Backend: server-less
iOS
Windows

server-less

Data scheme

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

SQL-like query language (OQL)

yes

close to SQL 92

yes

SQL-92 is not fully supported

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

Java Client API
Memcached protocol
RESTful HTTP API

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

.Net
All JVM based languages
C++
Groovy
Java
Scala

Progress proprietary ABL (Advanced Business Language)

.Net
Java

with Android only
Objective-C
React Native
Swift

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

user defined functions

yes

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Cache Event Listeners

yes

Change Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

since Version 11.4

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

Multi-source replication

Source-replica replication

none

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

Relationships in graphs

yes

Transaction concepts

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

ACID

yes, on a single node

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

In-Memory realm

yes

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Access rights per client and object definable

Users and groups

yes

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