DBMS > Realm vs. Spark SQL vs. STSdb vs. Transwarp KunDB vs. Ultipa

System Properties Comparison Realm vs. Spark SQL vs. STSdb vs. Transwarp KunDB vs. Ultipa

Editorial information provided by DB-Engines

Name

Description

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

High performance Graph DBMS supporting HTAP high availability cluster deployment

Primary database model

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

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Score	0.10
Rank	#344	Overall
	#151	Relational DBMS

Score	0.13
Rank	#335	Overall
	#31	Graph DBMS

Website

realm.io

spark.apache.org/sql

github.com/STSSoft/STSdb4

www.transwarp.cn/en/product/kundb

www.ultipa.com

Technical documentation

realm.io/docs

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

www.ultipa.com/document

Developer

Realm, acquired by MongoDB in May 2019

Apache Software Foundation

STS Soft SC

Transwarp

Ultipa

Initial release

2014

2011

2019

Current release

3.5.0 ( 2.13), September 2023

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPLv2, commercial license available

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

Scala

Server operating systems

Android
Backend: server-less
iOS
Windows

Linux
OS X
Windows

Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

yes

APIs and other access methods

JDBC
ODBC

.NET Client API

RESTful HTTP API

Supported programming languages

.Net
Java

with Android only
Objective-C
React Native
Swift

Java
Python
R
Scala

C#
Java

C++
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

runs within the applications so server-side scripts are unnecessary

yes

Triggers

yes

Change Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes, utilizing Spark Core

none

horizontal partitioning

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

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

In-Memory realm

User concepts

Access control

yes

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More resources

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