DBMS > 4D vs. Altibase vs. Drizzle vs. SpaceTime vs. Spark SQL

System Properties Comparison 4D vs. Altibase vs. Drizzle vs. SpaceTime vs. Spark SQL

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

Application development environment with integrated database management system

An enterprise grade, high-performance RDBMS

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

SpaceTime is a spatio-temporal DBMS with a focus on performance.

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

Primary database model

Relational DBMS

Spatial DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	1.07
Rank	#186	Overall
	#87	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

www.4d.com

altibase.com

www.mireo.com/spacetime

spark.apache.org/sql

Technical documentation

developer.4d.com

github.com/ALTIBASE/Documents/tree/master/Manuals

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

Developer

4D, Inc

Altibase

Drizzle project, originally started by Brian Aker

Mireo

Apache Software Foundation

Initial release

1984

1999

2008

2020

2014

Current release

v20, April 2023

v7.3, 2023, August 2023

7.2.4, September 2012

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

GNU GPL

commercial

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

C++

Scala

Server operating systems

OS X
Windows

AIX
HP-UX
Linux

FreeBSD
Linux
OS X

Linux

Linux
OS X
Windows

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

ANSI SQL-92

yes

with proprietary extensions

A subset of ANSI SQL is implemented

SQL-like DML and DDL statements

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
ODBC
Proprietary protocol

JDBC

RESTful HTTP API

JDBC
ODBC

Supported programming languages

4D proprietary IDE
PHP

C
C++
Java

C
C++
Java
PHP

C#
C++
Python

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

stored procedures and stored functions

Triggers

yes

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Fixed-grid hypercubes

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Multi-source replication
Source-replica replication

Real-time block device replication (DRBD)

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

User concepts

Access control

Users and groups

fine grained access rights according to SQL-standard

Pluggable authentication mechanisms

e.g. LDAP, HTTP

yes

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