DBMS > Amazon Redshift vs. Manticore Search vs. Stardog vs. TimesTen

System Properties Comparison Amazon Redshift vs. Manticore Search vs. Stardog vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Multi-storage database for search, including full-text search.

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

In-Memory RDBMS compatible to Oracle

Primary database model

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

aws.amazon.com/redshift

manticoresearch.com

www.stardog.com

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

Technical documentation

docs.aws.amazon.com/redshift

manual.manticoresearch.com

docs.stardog.com

docs.oracle.com/database/timesten-18.1

Developer

Amazon (based on PostgreSQL)

Manticore Software

Stardog-Union

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2012

2017

2010

1998

Current release

6.0, February 2023

7.3.0, May 2020

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

GPL version 2

commercial

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

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

C++

Java

Server operating systems

hosted

FreeBSD
Linux
macOS
Windows

Linux
macOS
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

Fixed schema

schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

Import/export of XML data possible

Secondary indexes

restricted

yes

full-text index on all search fields

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

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

yes

APIs and other access methods

JDBC
ODBC

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

All languages supporting JDBC/ODBC

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

user defined functions and aggregates, HTTP Server extensions in Java

PL/SQL

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Partitioning is done manually, search queries against distributed index is supported

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous replication based on Galera library

Multi-source replication in HA-Cluster

Multi-source replication
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

Immediate Consistency in HA-Cluster

Immediate Consistency or Eventual Consistency depending on configuration

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

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

yes

by means of logfiles and checkpoints

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

Access rights for users and roles

fine grained access rights according to SQL-standard

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