DBMS > LeanXcale vs. OpenQM vs. Qdrant vs. SpatiaLite vs. TerminusDB

System Properties Comparison LeanXcale vs. OpenQM vs. Qdrant vs. SpatiaLite vs. TerminusDB

Editorial information provided by DB-Engines

Name

Description

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

QpenQM is a high-performance, self-tuning, multi-value DBMS

A high-performance vector database with neural network or semantic-based matching

Spatial extension of SQLite

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

Primary database model

Key-value store
Relational DBMS

Secondary database models

Relational DBMS

Document store
RDF store

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

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Score	1.28
Rank	#167	Overall
	#7	Vector DBMS

Score	1.63
Rank	#146	Overall
	#3	Spatial DBMS

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

www.leanxcale.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

github.com/qdrant/qdrant
qdrant.tech

www.gaia-gis.it/fossil/libspatialite/index

terminusdb.com

Technical documentation

qdrant.tech/documentation

www.gaia-gis.it/gaia-sins/spatialite_topics.html

terminusdb.github.io/terminusdb/#

Developer

LeanXcale

Rocket Software, originally Martin Phillips

Qdrant

Alessandro Furieri

DataChemist Ltd.

Initial release

2015

1993

2021

2008

2018

Current release

3.4-12

5.0.0, August 2020

11.0.0, January 2023

License

Commercial or Open Source

commercial

Open Source

GPLv2, extended commercial license available

Open Source

Apache Version 2.0

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

Open Source

GPL V3

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

Rust

C++

Prolog, Rust

Server operating systems

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Docker
Linux
macOS
Windows

server-less

Linux

Data scheme

yes

with some exceptions

schema-free

yes

Typing

predefined data types such as float or date

Numbers, Strings, Geo, 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.

yes

Secondary indexes

yes

Keywords, numberic ranges, geo, full-text

yes

SQL

Support of SQL

yes

through Apache Derby

yes

SQL-like query language (WOQL)

APIs and other access methods

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

C
Java
Scala

.Net
Basic
C
Java
Objective C
PHP
Python

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

JavaScript
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

none

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Collection-level replication

none

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights can be defined down to the item level

Key-based authentication

Role-based access control

More information provided by the system vendor

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

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

Recent citations in the news

Open source vector database startup Qdrant raises $28M
23 January 2024, TechCrunch

Qdrant Announces an Industry-First Hybrid Cloud Offering For Enterprise AI Applications
16 April 2024, Business Wire

Qdrant Hybrid Cloud is Now Available for OCI Customers: Managed Vector Search Engine for Data-Sensitive AI ...
16 April 2024, blogs.oracle.com

Qdrant offers managed vector database for hybrid clouds
16 April 2024, InfoWorld

Why Vector Data Services For AI Are A Moveable Feast
17 April 2024, Forbes

provided by Google News

How TerminusDB is commercializing its open source graph database
16 March 2021, VentureBeat

TerminusDB Takes on Data Collaboration with a git-Like Approach
1 December 2020, The New Stack

Trinity College spinout TerminusDB secures €3.6m in investment
15 March 2021, The Irish Times

[MCR2030-CAMS-ARISE-UNDRR Webinar] Preventing cascading failures of critical assets: Using the Open-Source ...
12 April 2022, United Nations Office for Disaster Risk Reduction

Irish start-ups received €28m from Enterprise Ireland in 2021
7 April 2022, SiliconRepublic.com

provided by Google News

Share this page