DBMS > Lovefield vs. Memcached vs. SQLite vs. Stardog vs. Valentina Server

System Properties Comparison Lovefield vs. Memcached vs. SQLite vs. Stardog vs. Valentina Server

Editorial information provided by DB-Engines

Name

Description

Embeddable relational database for web apps written in pure JavaScript

In-memory key-value store, originally intended for caching

Widely used embeddable, in-process RDBMS

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

Object-relational database and reports server

Primary database model

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

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	19.42
Rank	#32	Overall
	#4	Key-value stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

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

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Website

google.github.io/lovefield

Technical documentation

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

github.com/memcached/memcached/wiki

www.sqlite.org/docs.html

docs.stardog.com

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Google

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Dwayne Richard Hipp

Stardog-Union

Paradigma Software

Initial release

2014

2003

2000

2010

1999

Current release

2.1.12, February 2017

1.6.25, March 2024

3.45.3 (15 April 2024), April 2024

7.3.0, May 2020

5.7.5

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD license

Open Source

Public Domain

commercial

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

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

JavaScript

Java

Server operating systems

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

tested with Chrome, Firefox, IE, Safari

FreeBSD
Linux
OS X
Unix
Windows

server-less

Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

dynamic column types

schema-free and OWL/RDFS-schema support

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.

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

yes

SQL-92 is not fully supported

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

yes

APIs and other access methods

Proprietary protocol

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

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

ODBC

Supported programming languages

JavaScript

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

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

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

user defined functions and aggregates, HTTP Server extensions in Java

yes

Triggers

Using read-only observers

yes

via event handlers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Repcached, a Memcached patch, provides this functionallity

none

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 in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

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, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

yes

using SASL (Simple Authentication and Security Layer) protocol

Access rights for users and roles

fine grained access rights according to SQL-standard

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