DBMS > Machbase Neo vs. OushuDB vs. Realm vs. Spark SQL vs. Trafodion

System Properties Comparison Machbase Neo vs. OushuDB vs. Realm vs. Spark SQL vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

TimeSeries DBMS for AIoT and BigData

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

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

Transactional SQL-on-Hadoop DBMS

Primary database model

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

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	0.04
Rank	#363	Overall
	#154	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

machbase.com

www.oushu.com/product/oushuDB

realm.io

spark.apache.org/sql

trafodion.apache.org

Technical documentation

machbase.com/dbms

www.oushu.com/documentation

realm.io/docs

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

trafodion.apache.org/documentation.html

Developer

Machbase

Oushu

Realm, acquired by MongoDB in May 2019

Apache Software Foundation

Apache Software Foundation, originally developed by HP

Initial release

2013

2014

Current release

V8.0, August 2023

4.0.1, August 2020

3.5.0 ( 2.13), September 2023

2.3.0, February 2019

License

Commercial or Open Source

commercial

free test version available

commercial

Open Source

Apache 2.0

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

C++, Java

Server operating systems

Linux
macOS
Windows

Linux

Android
Backend: server-less
iOS
Windows

Linux
OS X
Windows

Linux

Data scheme

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 query language

Full-featured ANSI SQL support

SQL-like DML and DDL statements

yes

APIs and other access methods

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

JDBC
ODBC

ADO.NET
JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

C
C++

.Net
Java

with Android only
Objective-C
React Native
Swift

Java
Python
R
Scala

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

runs within the applications so server-side scripts are unnecessary

Java Stored Procedures

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

yes, utilizing Spark Core

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

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

In-memory capabilities

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

yes

volatile and lookup table

yes

In-Memory realm

User concepts

Access control

simple password-based access control

Kerberos, SSL and role based access

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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