DBMS > mSQL vs. OrigoDB vs. SAP HANA vs. Spark SQL

System Properties Comparison mSQL vs. OrigoDB vs. SAP HANA vs. Spark SQL

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

mSQL (Mini SQL) is a simple and lightweight RDBMS

A fully ACID in-memory object graph database

In-memory, column based data store. Available as appliance or cloud service

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

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.67
Rank	#151	Overall
	#70	Relational DBMS

Score	0.03
Rank	#378	Overall
	#51	Document stores
	#18	Object oriented DBMS

Score	45.84
Rank	#22	Overall
	#16	Relational DBMS

Score	19.15
Rank	#33	Overall
	#20	Relational DBMS

Website

hughestech.com.au/products/msql

origodb.com

www.sap.com/products/hana.html

spark.apache.org/sql

Technical documentation

origodb.com/docs

help.sap.com/hana

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

Developer

Hughes Technologies

Robert Friberg et al

SAP

Apache Software Foundation

Initial release

1994

2009

under the name LiveDB

2010

2014

Current release

4.4, October 2021

2.0 SPS07 (April 4, 2023), April 2023

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

free licenses can be provided

Open Source

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

also available as a cloud based 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

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

Linux
Windows

Appliance or cloud-service

Linux
OS X
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

A subset of ANSI SQL is implemented

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

yes

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

.NET Client API
HTTP API
LINQ

JDBC
ODBC

Supported programming languages

C
C++
Delphi
Java
Perl
PHP
Tcl

.Net

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

SQLScript, R

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

client side managed; servers are not synchronized

yes

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

yes

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

depending on model

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

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

Role based authorization

yes

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.