DBMS > IBM Db2 vs. RethinkDB vs. Snowflake vs. Teradata

System Properties Comparison IBM Db2 vs. RethinkDB vs. Snowflake vs. Teradata

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Editorial information provided by DB-Engines

Name

Description

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

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Cloud-based data warehousing service for structured and semi-structured data

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Relational DBMS

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

Document store

Relational DBMS

Secondary database models

Document store
RDF store

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

with Db2 Spatial Extender

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	125.90
Rank	#9	Overall
	#6	Relational DBMS

Score	2.66
Rank	#107	Overall
	#20	Document stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Website

www.ibm.com/products/db2

rethinkdb.com

www.snowflake.com

www.teradata.com

Technical documentation

www.ibm.com/docs/en/db2

rethinkdb.com/docs

docs.snowflake.net/manuals/index.html

docs.teradata.com

Developer

IBM

The Linux Foundation

since July 2017

Snowflake Computing Inc.

Teradata

Initial release

1983

host version

2009

2014

1984

Current release

12.1, October 2016

2.4.1, August 2020

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

free version is available

Open Source

Apache Version 2

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C and C++

C++

Server operating systems

AIX
HP-UX
Linux
Solaris
Windows
z/OS

Linux
OS X
Windows

hosted

hosted
Linux

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

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

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

yes

SQL 2016 + extensions

APIs and other access methods

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

CLI Client
JDBC
ODBC

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

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

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

JavaScript (Node.js)
Python

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

yes

user defined functions

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Client-side triggers through changefeeds

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

only with Windows/Unix/Linux Version

Sharding

range based

yes

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes

with separate tools (MQ, InfoSphere)

Source-replica replication

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

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

fine grained access rights according to SQL-standard

yes

users and table-level permissions

Users with fine-grained authorization concept, user roles and pluggable authentication

fine grained access rights according to SQL-standard

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