DBMS > IBM Db2 vs. Lovefield vs. Memcached vs. Microsoft SQL Server vs. Trafodion

System Properties Comparison IBM Db2 vs. Lovefield vs. Memcached vs. Microsoft SQL Server vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Common in IBM host environments, 2 different versions for host and Windows/Linux

Embeddable relational database for web apps written in pure JavaScript

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

Microsofts flagship relational DBMS

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

Document store
Graph DBMS
Spatial DBMS

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

Score	128.46
Rank	#8	Overall
	#5	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

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

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

www.ibm.com/products/db2

google.github.io/lovefield

www.memcached.org

www.microsoft.com/en-us/sql-server

trafodion.apache.org

Technical documentation

www.ibm.com/docs/en/db2

github.com/google/lovefield/blob/master/docs/spec_index.md

github.com/memcached/memcached/wiki

learn.microsoft.com/en-US/sql/sql-server

trafodion.apache.org/documentation.html

Developer

IBM

Google

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Microsoft

Apache Software Foundation, originally developed by HP

Initial release

1983

host version

2014

2003

1989

2014

Current release

12.1, October 2016

2.1.12, February 2017

1.6.25, March 2024

SQL Server 2022, November 2022

2.3.0, February 2019

License

Commercial or Open Source

commercial

free version is available

Open Source

Apache 2.0

Open Source

BSD license

commercial

restricted free version is available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

JavaScript

C++

C++, Java

Server operating systems

AIX
HP-UX
Linux
Solaris
Windows
z/OS

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

FreeBSD
Linux
OS X
Unix
Windows

Linux
Windows

Linux

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

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

Proprietary protocol

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

ADO.NET
JDBC
ODBC

Supported programming languages

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

JavaScript

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Java Stored Procedures

Triggers

yes

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

only with Windows/Unix/Linux Version

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

with separate tools (MQ, InfoSphere)

none

Repcached, a Memcached patch, provides this functionallity

yes, but depending on the SQL-Server Edition

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

using SASL (Simple Authentication and Security Layer) protocol

fine grained access rights according to SQL-standard

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