DBMS > LevelDB vs. RDF4J vs. Sequoiadb vs. SQLite vs. SQream DB

System Properties Comparison LevelDB vs. RDF4J vs. Sequoiadb vs. SQLite vs. SQream DB

Editorial information provided by DB-Engines

Name

Description

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

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

NewSQL database with distributed OLTP and SQL

Widely used embeddable, in-process RDBMS

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Key-value store

RDF store

Document store
Relational DBMS

Relational DBMS

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

Score	2.75
Rank	#107	Overall
	#19	Key-value stores

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Score	0.48
Rank	#260	Overall
	#41	Document stores
	#121	Relational DBMS

Score	116.01
Rank	#10	Overall
	#7	Relational DBMS

Score	0.73
Rank	#228	Overall
	#105	Relational DBMS

Website

github.com/google/leveldb

Technical documentation

github.com/google/leveldb/blob/main/doc/index.md

rdf4j.org/documentation

www.sequoiadb.com/en/index.php?m=Files&a=index

www.sqlite.org/docs.html

docs.sqream.com

Developer

Google

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

Sequoiadb Ltd.

Dwayne Richard Hipp

SQream Technologies

Initial release

2011

2004

2013

2000

2017

Current release

1.23, February 2021

3.45.3 (15 April 2024), April 2024

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

BSD

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Server: AGPL; Client: Apache V2

Open Source

Public Domain

commercial

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

C++

Java

C++

C++, CUDA, Haskell, Java, Scala

Server operating systems

Illumos
Linux
OS X
Windows

Linux
OS X
Unix
Windows

Linux

server-less

Linux

Data scheme

schema-free

yes

RDF Schemas

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

yes

not rigid because of 'dynamic typing' concept.

yes, ANSI Standard SQL Types

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

yes

SQL-92 is not fully supported

yes

APIs and other access methods

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

proprietary protocol using JSON

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

.Net
JDBC
ODBC

Supported programming languages

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Java
PHP
Python

.Net
C++
Java
PHP
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

JavaScript

user defined functions in Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

Immediate Consistency

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

Document is locked during a transaction

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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

simple password-based access control

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