DBMS > Infobright vs. RDF4J vs. Transwarp ArgoDB vs. Weaviate

System Properties Comparison Infobright vs. RDF4J vs. Transwarp ArgoDB vs. Weaviate

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Editorial information provided by DB-Engines

Name

Description

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Distributed Analytical Database to replace Hadoop+MPP hybrid architecture

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

Primary database model

Secondary database models

Search engine

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

Score	1.02
Rank	#192	Overall
	#90	Relational DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	0.12
Rank	#348	Overall
	#151	Relational DBMS

Score	1.52
Rank	#153	Overall
	#6	Vector DBMS

Website

ignitetech.com/softwarelibrary/infobrightdb

rdf4j.org

www.transwarp.cn/en/product/argodb

github.com/weaviate/weaviate
weaviate.io

Technical documentation

rdf4j.org/documentation

docs.transwarp.cn/#/documents-support/docs?category=ARGODB

weaviate.io/developers/weaviate

Developer

Ignite Technologies Inc.; formerly InfoBright Inc.

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Transwarp

Weaviate B.V.

Initial release

2005

2004

2019

Current release

1.19, May 2023

License

Commercial or Open Source

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

Open Source

commercial license available with Weaviate Enterprise

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

Linux
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

RDF Schemas

yes

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

Knowledge Grid Technology used instead

yes

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

SQL

Support of SQL

yes

GraphQL is used as query language

APIs and other access methods

ADO.NET
JDBC
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Java
PHP
Python

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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

exploiting MySQL or PostgreSQL frontend capabilities

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,...
» more

Competitive advantages

Flexible deployment - Free, open source or fully-managed cloud vector database service...
» more

Typical application scenarios

As a database supporting the development of generative AI and semantic search applications...
» more

Key customers

All companies that have data.
» more

Market metrics

As of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
» more

Licensing and pricing models

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

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

Weaviate, an ANN Database with CRUD support
2 February 2021, Etienne Dilocker, SeMI Technologies (sponsor)

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