DBMS > Amazon DynamoDB vs. BaseX vs. KairosDB vs. Teradata Aster

System Properties Comparison Amazon DynamoDB vs. BaseX vs. KairosDB vs. Teradata Aster

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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

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

Distributed Time Series DBMS based on Cassandra or H2

Platform for big data analytics on multistructured data sources and types

Primary database model

Document store
Key-value store

Native XML DBMS

Time Series DBMS

Relational DBMS

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	1.84
Rank	#135	Overall
	#4	Native XML DBMS

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Website

aws.amazon.com/dynamodb

basex.org

github.com/kairosdb/kairosdb

Technical documentation

docs.aws.amazon.com/dynamodb

docs.basex.org

kairosdb.github.io

Developer

Amazon

BaseX GmbH

Teradata

Initial release

2012

2007

2013

2005

Current release

11.0, June 2024

1.2.2, November 2018

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

BSD license

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

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Database as a Service

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Implementation language

Java

Server operating systems

hosted

Linux
OS X
Windows

Linux

Data scheme

schema-free

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

XQuery supports types

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

APIs and other access methods

RESTful HTTP API

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

Graphite protocol
HTTP REST
Telnet API

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

Java
JavaScript

Node.js
PHP
Python

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

yes

R packages

Triggers

yes

by integration with AWS Lambda

yes

via events

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

selectable replication factor

based on Cassandra

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

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

multiple readers, single writer

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

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

Users with fine-grained authorization concept on 4 levels

simple password-based access control

fine grained access rights according to SQL-standard

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