DBMS > LevelDB vs. RDF4J vs. SAP HANA vs. Sequoiadb vs. Stardog

System Properties Comparison LevelDB vs. RDF4J vs. SAP HANA vs. Sequoiadb vs. Stardog

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.

In-memory, column based data store. Available as appliance or cloud service

NewSQL database with distributed OLTP and SQL

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

Primary database model

Key-value store

RDF store

Relational DBMS

Document store
Relational DBMS

Graph DBMS
RDF store

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

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

Website

github.com/google/leveldb

rdf4j.org

www.sap.com/products/hana.html

www.sequoiadb.com

www.stardog.com

Technical documentation

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

rdf4j.org/documentation

help.sap.com/hana

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

docs.stardog.com

Developer

Google

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

SAP

Sequoiadb Ltd.

Stardog-Union

Initial release

2011

2004

2010

2013

2010

Current release

1.23, February 2021

2.0 SPS07 (April 4, 2023), April 2023

7.3.0, May 2020

License

Commercial or Open Source

Open Source

BSD

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

Open Source

Server: AGPL; Client: Apache V2

commercial

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

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java

C++

Java

Server operating systems

Illumos
Linux
OS X
Windows

Linux
OS X
Unix
Windows

Appliance or cloud-service

Linux

Linux
macOS
Windows

Data scheme

schema-free

yes

RDF Schemas

yes

schema-free

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

SQL-like query language

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

APIs and other access methods

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

JDBC
ODBC

proprietary protocol using JSON

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

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

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

yes

SQLScript, R

JavaScript

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

none

yes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Source-replica replication

Multi-source replication in HA-Cluster

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 in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

ACID

Isolation support depends on the API used

ACID

Document is locked during a transaction

ACID

Concurrency

Support for concurrent manipulation of data

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

yes

simple password-based access control

Access rights for users and roles

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