DBMS > Realm vs. Spark SQL vs. STSdb vs. SWC-DB vs. TimesTen

System Properties Comparison Realm vs. Spark SQL vs. STSdb vs. SWC-DB vs. TimesTen

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

A high performance, scalable Wide Column DBMS

In-Memory RDBMS compatible to Oracle

Primary database model

Secondary database models

Time Series DBMS

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	0.01
Rank	#376	Overall
	#13	Wide column stores

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

realm.io

spark.apache.org/sql

github.com/STSSoft/STSdb4

github.com/kashirin-alex/swc-db
www.swcdb.org

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

realm.io/docs

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

docs.oracle.com/database/timesten-18.1

Developer

Realm, acquired by MongoDB in May 2019

Apache Software Foundation

STS Soft SC

Alex Kashirin

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2014

2011

2020

1998

Current release

3.5.0 ( 2.13), September 2023

4.0.8, September 2015

0.5, April 2021

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPLv2, commercial license available

Open Source

GPL V3

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

C++

Server operating systems

Android
Backend: server-less
iOS
Windows

Linux
OS X
Windows

Windows

Linux

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

Data scheme

yes

schema-free

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

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC

.NET Client API

Proprietary protocol
Thrift

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

.Net
Java

with Android only
Objective-C
React Native
Swift

Java
Python
R
Scala

C#
Java

C++

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

runs within the applications so server-side scripts are unnecessary

PL/SQL

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

none

yes, utilizing Spark Core

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

by means of logfiles and checkpoints

In-memory capabilities

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

yes

In-Memory realm

yes

User concepts

Access control

yes

fine grained access rights according to SQL-standard

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