DBMS > LeanXcale vs. mSQL vs. OrigoDB vs. RDF4J vs. Weaviate

System Properties Comparison LeanXcale vs. mSQL vs. OrigoDB vs. RDF4J vs. Weaviate

Editorial information provided by DB-Engines

Name

Description

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

mSQL (Mini SQL) is a simple and lightweight RDBMS

A fully ACID in-memory object graph database

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

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

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Document store
Object oriented DBMS

RDF store

Vector DBMS

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

Score	0.35
Rank	#283	Overall
	#41	Key-value stores
	#128	Relational DBMS

Score	1.67
Rank	#151	Overall
	#70	Relational DBMS

Score	0.03
Rank	#378	Overall
	#51	Document stores
	#18	Object oriented DBMS

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Score	1.89
Rank	#138	Overall
	#4	Vector DBMS

Website

www.leanxcale.com

hughestech.com.au/products/msql

origodb.com

rdf4j.org

github.com/weaviate/weaviate
weaviate.io

Technical documentation

origodb.com/docs

rdf4j.org/documentation

weaviate.io/developers/weaviate

Developer

LeanXcale

Hughes Technologies

Robert Friberg et al

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

Weaviate B.V.

Initial release

2015

1994

2009

under the name LiveDB

2004

2019

Current release

4.4, October 2021

1.19, May 2023

License

Commercial or Open Source

commercial

free licenses can be provided

Open Source

Eclipse Distribution License (EDL), v1.0.

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

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

Linux
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

RDF Schemas

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

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

SQL

Support of SQL

yes

through Apache Derby

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

GraphQL is used as query language

APIs and other access methods

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

JDBC
ODBC

.NET Client API
HTTP API
LINQ

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

C
Java
Scala

C
C++
Delphi
Java
Perl
PHP
Tcl

.Net

Java
PHP
Python

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

client side managed; servers are not synchronized

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

none

Eventual Consistency

Foreign keys

Referential integrity

yes

depending on model

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

Write ahead log

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

Role based authorization

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

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.

Related products and services

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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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