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

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

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

A relational database management system that stores data in columns

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

An AI-native realtime vector database engine that integrates scalable machine learning models.

Primary database model

Secondary database models

Document store
Spatial DBMS

Document store
RDF store

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Score	1.52
Rank	#153	Overall
	#6	Vector DBMS

Website

aws.amazon.com/redshift

www.monetdb.org

terminusdb.com

www.warp10.io

github.com/weaviate/weaviate
weaviate.io

Technical documentation

docs.aws.amazon.com/redshift

www.monetdb.org/Documentation

terminusdb.github.io/terminusdb/#

www.warp10.io/content/02_Getting_started

weaviate.io/developers/weaviate

Developer

Amazon (based on PostgreSQL)

MonetDB BV

DataChemist Ltd.

SenX

Weaviate B.V.

Initial release

2012

2004

2018

2015

2019

Current release

Dec2023 (11.49), December 2023

11.0.0, January 2023

1.19, May 2023

License

Commercial or Open Source

commercial

Open Source

Mozilla Public License 2.0

Open Source

GPL V3

Open Source

Apache License 2.0

Open Source

commercial license available with Weaviate Enterprise

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

Prolog, Rust

Java

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes

string, int, float, geo point, date, cross reference, fuzzy references

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.

Secondary indexes

restricted

yes

all data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL 2003 with some extensions

SQL-like query language (WOQL)

GraphQL is used as query language

APIs and other access methods

JDBC
ODBC

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

HTTP API
Jupyter
WebSocket

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC

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

JavaScript
Python

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

user defined functions

in Python

yes, in SQL, C, R

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding via remote tables

Graph Partitioning

Sharding

based on HBase

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication available in experimental status

Journaling Streams

selectable replication factor

based on HBase

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

Eventual Consistency

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

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

Role-based access control

Mandatory use of cryptographic tokens, containing fine-grained authorizations

API Keys
OpenID Connect Discovery

More information provided by the system vendor

Specific characteristics

Weaviate is an open source vector database that is robust, scalable, cloud-native,...
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Competitive advantages

Flexible deployment - Free, open source or fully-managed cloud vector database service...
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Typical application scenarios

As a database supporting the development of generative AI and semantic search applications...
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Key customers

All companies that have data.
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Market metrics

As of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
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Licensing and pricing models

Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
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