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

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

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

A widely used distributed, scalable search engine based on Apache Lucene

Primary database model

Key-value store

RDF store

Relational DBMS

Document store
Relational DBMS

Search engine

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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	42.91
Rank	#24	Overall
	#3	Search engines

Website

github.com/google/leveldb

rdf4j.org

www.sap.com/products/hana.html

www.sequoiadb.com

solr.apache.org

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

solr.apache.org/resources.html

Developer

Google

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

SAP

Sequoiadb Ltd.

Apache Software Foundation

Initial release

2011

2004

2010

2013

2006

Current release

1.23, February 2021

2.0 SPS07 (April 4, 2023), April 2023

9.5.0, February 2024

License

Commercial or Open Source

Open Source

BSD

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

Open Source

Server: AGPL; Client: Apache V2

Open Source

Apache Version 2

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

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

schema-free

yes

RDF Schemas

yes

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

yes

supports customizable data types and automatic typing

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.

yes

Secondary indexes

yes

All search fields are automatically indexed

SQL

Support of SQL

yes

SQL-like query language

Solr Parallel SQL Interface

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

Java API
RESTful HTTP/JSON API

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
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

SQLScript, R

JavaScript

Java plugins

Triggers

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

none

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual 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

ACID

Document is locked during a transaction

optimistic locking

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

yes

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