DBMS > Lovefield vs. Prometheus vs. RDF4J vs. SurrealDB

System Properties Comparison Lovefield vs. Prometheus vs. RDF4J vs. SurrealDB

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Editorial information provided by DB-Engines

Name

Description

Embeddable relational database for web apps written in pure JavaScript

Open-source Time Series DBMS and monitoring system

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

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

Primary database model

Relational DBMS

Time Series DBMS

RDF store

Document store
Graph DBMS

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

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	7.69
Rank	#50	Overall
	#3	Time Series DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

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

Website

google.github.io/lovefield

prometheus.io

rdf4j.org

surrealdb.com

Technical documentation

github.com/google/lovefield/blob/master/docs/spec_index.md

prometheus.io/docs

rdf4j.org/documentation

surrealdb.com/docs

Developer

Google

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

SurrealDB Ltd

Initial release

2014

2015

2004

2022

Current release

2.1.12, February 2017

v1.5.0, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

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

JavaScript

Java

Rust

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
Windows

Linux
OS X
Unix
Windows

Linux
macOS
Windows

Data scheme

yes

RDF Schemas

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

SQL-like query language

APIs and other access methods

RESTful HTTP/JSON API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

GraphQL
RESTful HTTP API
WebSocket

Supported programming languages

JavaScript

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

Java
PHP
Python

Deno
Go
JavaScript (Node.js)
Rust

Server-side scripts

Stored procedures

yes

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

by Federation

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes, by using IndexedDB or the cloud service Firebase Realtime Database

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

using MemoryDB

User concepts

Access control

yes, based on authentication and database rules

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