DBMS > Memcached vs. SAP IQ vs. Spark SQL vs. Transbase

System Properties Comparison Memcached vs. SAP IQ vs. Spark SQL vs. Transbase

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Editorial information provided by DB-Engines

Name

Description

In-memory key-value store, originally intended for caching

Columnar RDBMS optimized for Big Data analytics

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

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Key-value store

Relational DBMS

column-oriented

Relational DBMS

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

Score	19.42
Rank	#32	Overall
	#4	Key-value stores

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

www.memcached.org

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

spark.apache.org/sql

www.transaction.de/en/products/transbase.html

Technical documentation

github.com/memcached/memcached/wiki

help.sap.com/docs/SAP_IQ

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

www.transaction.de/en/products/transbase/features.html

Developer

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

SAP, formerly Sybase

Apache Software Foundation

Transaction Software GmbH

Initial release

2003

1994

2014

1987

Current release

1.6.25, March 2024

16.1 SPS04, April 2019

3.5.0 ( 2.13), September 2023

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

BSD license

commercial

Open Source

Apache 2.0

commercial

free development license

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 and C++

Server operating systems

FreeBSD
Linux
OS X
Unix
Windows

AIX
HP-UX
Linux
Solaris
Windows

Linux
OS X
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

Proprietary protocol

ADO.NET
JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

C
C#
C++
Java
Perl
PHP
Python
Ruby

Java
Python
R
Scala

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

shared disk or shared nothing architectures with SAP IQ Multiplexer

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

none

Repcached, a Memcached patch, provides this functionallity

SAP/Sybase Replication Server

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

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

yes

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

yes

using SASL (Simple Authentication and Security Layer) protocol

fine grained access rights according to SQL-standard

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More resources

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Redis extends the lead in the DB-Engines key-value store ranking
3 February 2014, Matthias Gelbmann

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3 October 2012, Matthias Gelbmann, Paul Andlinger

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