DBMS > SAP IQ vs. SpaceTime vs. Spark SQL vs. STSdb vs. ToroDB

System Properties Comparison SAP IQ vs. SpaceTime vs. Spark SQL vs. STSdb vs. ToroDB

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Columnar RDBMS optimized for Big Data analytics

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

column-oriented

Secondary database models

Relational DBMS

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

Score	2.64
Rank	#108	Overall
	#52	Relational DBMS

Score	0.03
Rank	#392	Overall
	#8	Spatial DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

www.mireo.com/spacetime

spark.apache.org/sql

github.com/STSSoft/STSdb4

github.com/torodb/server

Technical documentation

help.sap.com/docs/SAP_IQ

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

Developer

SAP, formerly Sybase

Mireo

Apache Software Foundation

STS Soft SC

8Kdata

Initial release

1994

2020

2014

2011

2016

Current release

16.1 SPS04, April 2019

3.5.0 ( 2.13), September 2023

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GPLv2, commercial license available

Open Source

AGPL-V3

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

Java

Server operating systems

AIX
HP-UX
Linux
Solaris
Windows

Linux

Linux
OS X
Windows

Windows

All OS with a Java 7 VM

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

yes

string, integer, double, boolean, date, object_id

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

yes

A subset of ANSI SQL is implemented

SQL-like DML and DDL statements

APIs and other access methods

ADO.NET
JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

JDBC
ODBC

.NET Client API

Supported programming languages

C
C#
C++
Java
Perl
PHP
Python
Ruby

C#
C++
Python

Java
Python
R
Scala

C#
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

shared disk or shared nothing architectures with SAP IQ Multiplexer

Fixed-grid hypercubes

yes, utilizing Spark Core

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

SAP/Sybase Replication Server

Real-time block device replication (DRBD)

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
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.

User concepts

Access control

fine grained access rights according to SQL-standard

yes

Access rights for users and roles

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