DBMS > Amazon Redshift vs. KeyDB vs. SAP SQL Anywhere vs. Stardog vs. TerminusDB

System Properties Comparison Amazon Redshift vs. KeyDB vs. SAP SQL Anywhere vs. Stardog vs. TerminusDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Secondary database models

Document store
RDF store

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

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

Score	3.50
Rank	#81	Overall
	#44	Relational DBMS

Score	1.93
Rank	#121	Overall
	#10	Graph DBMS
	#6	RDF stores

Score	0.19
Rank	#311	Overall
	#27	Graph DBMS

Website

aws.amazon.com/redshift

github.com/Snapchat/KeyDB
keydb.dev

www.sap.com/products/technology-platform/sql-anywhere.html

www.stardog.com

terminusdb.com

Technical documentation

docs.aws.amazon.com/redshift

docs.keydb.dev

help.sap.com/docs/SAP_SQL_Anywhere

docs.stardog.com

terminusdb.github.io/terminusdb/#

Developer

Amazon (based on PostgreSQL)

EQ Alpha Technology Ltd.

SAP

formerly Sybase

Stardog-Union

DataChemist Ltd.

Initial release

2012

2019

1992

2010

2018

Current release

17, July 2015

7.3.0, May 2020

11.0.0, January 2023

License

Commercial or Open Source

commercial

Open Source

BSD-3

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Open Source

GPL V3

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++

Java

Prolog, Rust

Server operating systems

hosted

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows

Linux
macOS
Windows

Linux

Data scheme

yes

schema-free

yes

schema-free and OWL/RDFS-schema support

yes

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

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

Import/export of XML data possible

Secondary indexes

restricted

yes

by using the Redis Search module

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

SQL-like query language (WOQL)

APIs and other access methods

JDBC
ODBC

Proprietary protocol

RESP - REdis Serialization Protoco

ADO.NET
HTTP API
JDBC
ODBC

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

All languages supporting JDBC/ODBC

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

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

in Python

Lua

yes, in C/C++, Java, .Net or Perl

user defined functions and aggregates, HTTP Server extensions in Java

yes

Triggers

yes

via event handlers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Source-replica replication

Database mirroring

Multi-source replication in HA-Cluster

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

relationships in graphs

yes

Transaction concepts

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

ACID

Optimistic locking, atomic execution of commands blocks and scripts

ACID

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

yes

in-memory journaling

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

simple password-based access control and ACL

fine grained access rights according to SQL-standard

Access rights for users and roles

Role-based access control

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.