DBMS > Lovefield vs. OrientDB vs. SQLite vs. Teradata vs. Valentina Server

System Properties Comparison Lovefield vs. OrientDB vs. SQLite vs. Teradata vs. Valentina Server

Editorial information provided by DB-Engines

Name

Description

Embeddable relational database for web apps written in pure JavaScript

Multi-model DBMS (Document, Graph, Key/Value)

Widely used embeddable, in-process RDBMS

A hybrid cloud data analytics software platform (Teradata Vantage)

Object-relational database and reports server

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.32
Rank	#290	Overall
	#132	Relational DBMS

Score	3.27
Rank	#97	Overall
	#16	Document stores
	#6	Graph DBMS
	#15	Key-value stores

Score	116.01
Rank	#10	Overall
	#7	Relational DBMS

Score	47.84
Rank	#21	Overall
	#15	Relational DBMS

Score	0.18
Rank	#329	Overall
	#144	Relational DBMS

Website

google.github.io/lovefield

Technical documentation

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

www.orientdb.com/docs/last/index.html

www.sqlite.org/docs.html

docs.teradata.com

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

Developer

Google

OrientDB LTD; CallidusCloud; SAP

Dwayne Richard Hipp

Teradata

Paradigma Software

Initial release

2014

2010

2000

1984

1999

Current release

2.1.12, February 2017

3.2.29, March 2024

3.45.2 (12 March 2024), March 2024

Teradata Vantage 1.0 MU2, January 2019

5.7.5

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache version 2

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

JavaScript

Java

Server operating systems

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

tested with Chrome, Firefox, IE, Safari

All OS with a Java JDK (>= JDK 6)

server-less

hosted
Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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

Join-index to prejoin tables, aggregate index, sparse index, hash index

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

SQL-like query language, no joins

yes

SQL-92 is not fully supported

yes

SQL 2016 + extensions

yes

APIs and other access methods

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

ODBC

Supported programming languages

JavaScript

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

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++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

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

Server-side scripts

Stored procedures

Java, Javascript

yes

UDFs, stored procedures, table functions in parallel

yes

Triggers

Using read-only observers

Hooks

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship 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

Access rights for users and roles; record level security configurable

fine grained access rights according to SQL-standard

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