DBMS > Amazon Redshift vs. MonetDB vs. Solr vs. TerminusDB vs. Warp 10

System Properties Comparison Amazon Redshift vs. MonetDB vs. Solr vs. TerminusDB vs. Warp 10

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Name

Description

Large scale data warehouse service for use with business intelligence tools

A relational database management system that stores data in columns

A widely used distributed, scalable search engine based on Apache Lucene

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

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

Document store
RDF store

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Trend Chart

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	41.02
Rank	#24	Overall
	#3	Search engines

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

aws.amazon.com/redshift

Technical documentation

docs.aws.amazon.com/redshift

www.monetdb.org/Documentation

solr.apache.org/resources.html

terminusdb.github.io/terminusdb/#

www.warp10.io/content/02_Getting_started

Developer

Amazon (based on PostgreSQL)

MonetDB BV

Apache Software Foundation

DataChemist Ltd.

SenX

Initial release

2012

2004

2006

2018

2015

Current release

Dec2023 (11.49), December 2023

9.6.1, May 2024

11.0.0, January 2023

License

Commercial or Open Source

commercial

Open Source

Mozilla Public License 2.0

Open Source

Apache Version 2

Open Source

GPL V3

Open Source

Apache License 2.0

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

Java

Prolog, Rust

Java

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Linux

Linux
OS X
Windows

Data scheme

yes

Dynamic Fields enables on-the-fly addition of new fields

yes

schema-free

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

restricted

yes

All search fields are automatically indexed

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL 2003 with some extensions

Solr Parallel SQL Interface

SQL-like query language (WOQL)

APIs and other access methods

JDBC
ODBC

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Java API
RESTful HTTP/JSON API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

HTTP API
Jupyter
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC

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

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

in Python

yes, in SQL, C, R

Java plugins

yes

WarpScript

Triggers

yes

User configurable commands triggered on index changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding via remote tables

Sharding

Graph Partitioning

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication available in experimental status

yes

Journaling Streams

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

based on HBase

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

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory journaling

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

fine grained access rights according to SQL-standard

yes

Role-based access control

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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