DBMS > BoltDB vs. DataFS vs. Infobright vs. Lovefield

System Properties Comparison BoltDB vs. DataFS vs. Infobright vs. Lovefield

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Editorial information provided by DB-Engines

Name

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Key-value store

Object oriented DBMS

Relational DBMS

Secondary database models

Graph DBMS

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

Score	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Website

github.com/boltdb/bolt

newdatabase.com

ignitetech.com/softwarelibrary/infobrightdb

google.github.io/lovefield

Technical documentation

dev.mobiland.com/Overview.xsp

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

Developer

Mobiland AG

Ignite Technologies Inc.; formerly InfoBright Inc.

Google

Initial release

2013

2018

2005

2014

Current release

1.1.263, October 2022

2.1.12, February 2017

License

Commercial or Open Source

Open Source

MIT License

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

Apache 2.0

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

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Windows

Linux
Windows

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

tested with Chrome, Firefox, IE, Safari

Data scheme

schema-free

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

Typing

predefined data types such as float or date

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.

Secondary indexes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

ADO.NET
JDBC
ODBC

Supported programming languages

.Net
C
C#
C++
VB.Net

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

JavaScript

Server-side scripts

Stored procedures

Triggers

no, except callback-events from server when changes happened

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

Proprietary Sharding system

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

Windows-Profile

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

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