DBMS > Badger vs. DuckDB vs. GeoSpock vs. RDF4J

System Properties Comparison Badger vs. DuckDB vs. GeoSpock vs. RDF4J

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Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

An embeddable, in-process, column-oriented SQL OLAP RDBMS

Spatial and temporal data processing engine for extreme data scale

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

Primary database model

Key-value store

Relational DBMS

RDF store

Secondary database models

Time Series DBMS

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	4.63
Rank	#69	Overall
	#37	Relational DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Website

github.com/dgraph-io/badger

duckdb.org

geospock.com

rdf4j.org

Technical documentation

godoc.org/github.com/dgraph-io/badger

duckdb.org/docs

rdf4j.org/documentation

Developer

DGraph Labs

GeoSpock

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

Initial release

2017

2018

2004

Current release

1.0.0, June 2024

2.0, September 2019

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

MIT License

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

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

C++

Java, Javascript

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

server-less

hosted

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

temporal, categorical

yes

SQL

Support of SQL

yes

ANSI SQL for query only (using Presto)

APIs and other access methods

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

JDBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Automatic sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate 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

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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 for users can be defined per table

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