DBMS > AllegroGraph vs. Amazon Redshift vs. Amazon SimpleDB vs. EXASOL vs. KeyDB

System Properties Comparison AllegroGraph vs. Amazon Redshift vs. Amazon SimpleDB vs. EXASOL vs. KeyDB

Editorial information provided by DB-Engines

Name

Description

High performance, persistent RDF store with additional support for Graph DBMS

Large scale data warehouse service for use with business intelligence tools

Hosted simple database service by Amazon, with the data stored in the Amazon Cloud.

There is an unrelated product called SimpleDB developed by Edward Sciore

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Secondary database models

Spatial DBMS

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

Score	0.84
Rank	#204	Overall
	#35	Document stores
	#18	Graph DBMS
	#7	RDF stores
	#10	Vector DBMS

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	1.89
Rank	#128	Overall
	#22	Key-value stores

Score	1.66
Rank	#138	Overall
	#64	Relational DBMS

Score	0.63
Rank	#232	Overall
	#32	Key-value stores

Website

allegrograph.com

aws.amazon.com/redshift

aws.amazon.com/simpledb

www.exasol.com

github.com/Snapchat/KeyDB
keydb.dev

Technical documentation

franz.com/agraph/support/documentation/current/agraph-introduction.html

docs.aws.amazon.com/redshift

docs.aws.amazon.com/simpledb

www.exasol.com/resources

docs.keydb.dev

Developer

Franz Inc.

Amazon (based on PostgreSQL)

Amazon

Exasol

EQ Alpha Technology Ltd.

Initial release

2004

2012

2007

2000

2019

Current release

8.0, December 2023

License

Commercial or Open Source

commercial

Limited community edition free

commercial

Open Source

BSD-3

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

C++

Server operating systems

Linux
OS X
Windows

hosted

Linux

Data scheme

yes

RDF schemas

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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.

bulk load of XML files possible

Secondary indexes

yes

restricted

yes

All columns are indexed automatically

yes

by using the Redis Search module

SQL

Support of SQL

SPARQL is used as query language

yes

does not fully support an SQL-standard

yes

APIs and other access methods

RESTful HTTP API
SPARQL

JDBC
ODBC

RESTful HTTP API

.Net
JDBC
ODBC
WebSocket

Proprietary protocol

RESP - REdis Serialization Protoco

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

All languages supporting JDBC/ODBC

.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala

Java
Lua
Python
R

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

user defined functions

in Python

user defined functions

Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

with Federation

Sharding

none

Sharding must be implemented in the application

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

Concurrent data updates can be detected by the application

ACID

Optimistic locking, atomic execution of commands blocks and scripts

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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 with fine-grained authorization concept, user roles and pluggable authentication

fine grained access rights according to SQL-standard

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

Access rights for users, groups and roles according to SQL-standard

simple password-based access control and ACL

More information provided by the system vendor

News

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16 September 2024

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10 September 2024

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10 September 2024

Pruning Cycles in UMLS Metathesaurus: A Neuro Symbolic AI Approach
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Podcast – Gartner AI Hype Cycle – Knowledge Graphs and Neuro-Symbolic AI
24 August 2024

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