DBMS > 4D vs. Spark SQL vs. SWC-DB vs. TimesTen

System Properties Comparison 4D vs. Spark SQL vs. SWC-DB vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

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

A high performance, scalable Wide Column DBMS

In-Memory RDBMS compatible to Oracle

Primary database model

Relational DBMS

Wide column store

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

www.4d.com

spark.apache.org/sql

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

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

Technical documentation

developer.4d.com

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

docs.oracle.com/database/timesten-18.1

Developer

4D, Inc

Apache Software Foundation

Alex Kashirin

Oracle, TimesTen Performance Software, HP

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

Initial release

1984

2014

2020

1998

Current release

v20, April 2023

3.5.0 ( 2.13), September 2023

0.5, April 2021

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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

OS X
Windows

Linux
OS X
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

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

SQL-like DML and DDL statements

SQL-like query language

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
ODBC

Proprietary protocol
Thrift

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

4D proprietary IDE
PHP

Java
Python
R
Scala

C++

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes, utilizing Spark Core

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

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

User concepts

Access control

Users and groups

fine grained access rights according to SQL-standard

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