DBMS > RDF4J vs. RocksDB vs. SurrealDB vs. VictoriaMetrics

System Properties Comparison RDF4J vs. RocksDB vs. SurrealDB vs. VictoriaMetrics

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Editorial information provided by DB-Engines

Name

Description

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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

A fully ACID transactional, developer-friendly, multi-model DBMS

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Primary database model

RDF store

Key-value store

Document store
Graph DBMS

Time Series DBMS

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

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	1.02
Rank	#190	Overall
	#33	Document stores
	#18	Graph DBMS

Score	1.23
Rank	#172	Overall
	#15	Time Series DBMS

Website

Technical documentation

rdf4j.org/documentation

github.com/facebook/rocksdb/wiki

surrealdb.com/docs

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

Developer

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

Facebook, Inc.

SurrealDB Ltd

VictoriaMetrics

Initial release

2004

2013

2022

2018

Current release

9.2.1, May 2024

v1.5.0, May 2024

v1.91, May 2023

License

Commercial or Open Source

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

BSD

Open Source

Apache Version 2.0

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

C++

Rust

Server operating systems

Linux
OS X
Unix
Windows

Linux

Linux
macOS
Windows

FreeBSD
Linux
macOS
OpenBSD

Data scheme

yes

RDF Schemas

schema-free

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

SQL

Support of SQL

SQL-like query language

APIs and other access methods

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

C++ API
Java API

GraphQL
RESTful HTTP API
WebSocket

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

Supported programming languages

Java
PHP
Python

C
C++
Go
Java
Perl
Python
Ruby

Deno
Go
JavaScript (Node.js)
Rust

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Synchronous replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

yes

ACID

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

yes, based on authentication and database rules

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