DBMS > Amazon DynamoDB vs. IBM Db2 vs. jBASE vs. Microsoft Azure Synapse Analytics vs. Teradata Aster

System Properties Comparison Amazon DynamoDB vs. IBM Db2 vs. jBASE vs. Microsoft Azure Synapse Analytics vs. Teradata Aster

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

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

A robust multi-value DBMS comprising development tools and middleware

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Platform for big data analytics on multistructured data sources and types

Primary database model

Document store
Key-value store

Relational DBMS

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

Multivalue DBMS

Relational DBMS

Secondary database models

Document store
RDF store

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

with Db2 Spatial Extender

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	128.46
Rank	#8	Overall
	#5	Relational DBMS

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Website

aws.amazon.com/dynamodb

www.ibm.com/products/db2

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

azure.microsoft.com/services/synapse-analytics

Technical documentation

docs.aws.amazon.com/dynamodb

www.ibm.com/docs/en/db2

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

docs.microsoft.com/azure/synapse-analytics

Developer

Amazon

IBM

Rocket Software (formerly Zumasys)

Microsoft

Teradata

Initial release

2012

1983

host version

1991

2016

2005

Current release

12.1, October 2016

5.7

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

free version is available

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

hosted

AIX
HP-UX
Linux
Solaris
Windows
z/OS

AIX
Linux
Windows

hosted

Linux

Data scheme

schema-free

yes

schema-free

yes

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

Typing

predefined data types such as float or date

yes

optional

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

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

yes

Embedded SQL for jBASE in BASIC

yes

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

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

.Net
Basic
Jabbascript
Java

C#
Java
PHP

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

yes

Transact SQL

R packages

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

only with Windows/Unix/Linux Version

Sharding

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

with separate tools (MQ, InfoSphere)

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

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

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.