DBMS > LevelDB vs. RDFox vs. Snowflake vs. SQLite vs. TimesTen

System Properties Comparison LevelDB vs. RDFox vs. Snowflake vs. SQLite vs. TimesTen

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

High performance knowledge graph and semantic reasoning engine

Cloud-based data warehousing service for structured and semi-structured data

Widely used embeddable, in-process RDBMS

In-Memory RDBMS compatible to Oracle

Primary database model

Key-value store

Graph DBMS
RDF store

Relational DBMS

Secondary database models

Relational DBMS

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

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

Score	0.23
Rank	#308	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

github.com/google/leveldb

www.oxfordsemantic.tech

www.snowflake.com

www.sqlite.org

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

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

docs.oxfordsemantic.tech

docs.snowflake.net/manuals/index.html

www.sqlite.org/docs.html

docs.oracle.com/database/timesten-18.1

Developer

Google

Oxford Semantic Technologies

Snowflake Computing Inc.

Dwayne Richard Hipp

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2011

2017

2014

2000

1998

Current release

1.23, February 2021

6.0, Septermber 2022

3.45.3 (15 April 2024), April 2024

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

BSD

commercial

Open Source

Public Domain

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Server operating systems

Illumos
Linux
OS X
Windows

Linux
macOS
Windows

hosted

server-less

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

yes

RDF schemas

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-92 is not fully supported

yes

APIs and other access methods

RESTful HTTP API
SPARQL 1.1

CLI Client
JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C
Java

JavaScript (Node.js)
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
C++
Java
PL/SQL

Server-side scripts

Stored procedures

user defined functions

PL/SQL

Triggers

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

replication via a shared file system

yes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

by means of logfiles and checkpoints

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Roles, resources, and access types

Users with fine-grained authorization concept, user roles and pluggable authentication

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.