DBMS > ObjectBox vs. Qdrant vs. Stardog vs. UniData,UniVerse vs. Yanza

System Properties Comparison ObjectBox vs. Qdrant vs. Stardog vs. UniData,UniVerse vs. Yanza

Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Extremely fast embedded database for small devices, IoT and Mobile

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

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

MultiValue database and application server with SQL mapping layer and meta database capabilities

Time Series DBMS for IoT Applications

Primary database model

Secondary database models

Time Series DBMS

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

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	3.16
Rank	#97	Overall
	#2	Multivalue DBMS

Website

objectbox.io

github.com/qdrant/qdrant
qdrant.tech

www.stardog.com

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

yanza.com

Technical documentation

docs.objectbox.io

qdrant.tech/documentation

docs.stardog.com

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

ObjectBox Limited

Qdrant

Stardog-Union

Rocket Software

Yanza

Initial release

2017

2021

2010

1985

2015

Current release

7.3.0, May 2020

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache Version 2.0

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C and C++

Rust

Java

Server operating systems

Android
iOS
Linux
macOS
Windows

Docker
Linux
macOS
Windows

Linux
macOS
Windows

AIX
HP-UX
Linux
Solaris
Windows

Windows

Data scheme

yes

schema-free

schema-free and OWL/RDFS-schema support

schema-free

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

yes

optional

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.

Import/export of XML data possible

Secondary indexes

yes

Keywords, numberic ranges, geo, full-text

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

yes

APIs and other access methods

Proprietary native API

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

HTTP API

Supported programming languages

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

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

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

.Net
Basic

U2 Basic
C
Java

any language that supports HTTP calls

Server-side scripts

Stored procedures

user defined functions and aggregates, HTTP Server extensions in Java

yes

Triggers

yes

via event handlers

yes

U2 Basic

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

online/offline synchronization between client and server

Collection-level replication

Multi-source replication in HA-Cluster

Source-replica replication

none

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

Immediate Consistency in HA-Cluster

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

yes

Key-based authentication

Access rights for users and roles

Access rights according to SQL-standard and operating system based

More information provided by the system vendor

News

The first On-Device Vector Database: ObjectBox 4.0
16 May 2024

Edge AI: The era of on-device AI
23 April 2024

In-Memory Database Use Cases
15 February 2024

Data Viewer for Objects – announcing ObjectBox Admin
14 November 2023

Vector Databases for Edge AI
9 August 2023

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