DBMS > BigObject vs. DataFS vs. mSQL vs. Spark SQL

System Properties Comparison BigObject vs. DataFS vs. mSQL vs. Spark SQL

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

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.

mSQL (Mini SQL) is a simple and lightweight RDBMS

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Object oriented DBMS

Relational DBMS

Secondary database models

Graph DBMS

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	0.09
Rank	#360	Overall
	#17	Object oriented DBMS

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

bigobject.io

newdatabase.com

hughestech.com.au/products/msql

spark.apache.org/sql

Technical documentation

docs.bigobject.io

dev.mobiland.com/Overview.xsp

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

BigObject, Inc.

Mobiland AG

Hughes Technologies

Apache Software Foundation

Initial release

2015

2018

1994

2014

Current release

1.1.263, October 2022

4.4, October 2021

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

free community edition available

commercial

free licenses can be provided

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

Scala

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Windows

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

Linux
OS X
Windows

Data scheme

yes

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

yes

SQL

Support of SQL

SQL-like DML and DDL statements

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

SQL-like DML and DDL statements

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

.NET Client API
Proprietary client DLL
WinRT client

JDBC
ODBC

Supported programming languages

.Net
C
C#
C++
VB.Net

C
C++
Delphi
Java
Perl
PHP
Tcl

Java
Python
R
Scala

Server-side scripts

Stored procedures

Lua

Triggers

no, except callback-events from server when changes happened

Partitioning methods

Methods for storing different data on different nodes

none

Proprietary Sharding system

none

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

none

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

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

Windows-Profile

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