DBMS > Amazon DynamoDB vs. Datomic vs. FileMaker vs. InterSystems Caché vs. Teradata Aster

System Properties Comparison Amazon DynamoDB vs. Datomic vs. FileMaker vs. InterSystems Caché vs. Teradata Aster

Editorial information provided by DB-Engines

Name

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

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

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

FileMaker is a cross-platform RDBMS that includes a GUI frontend.

A multi-model DBMS and application server

Platform for big data analytics on multistructured data sources and types

Primary database model

Document store
Key-value store

Relational DBMS

Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Secondary database models

Document store

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	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	47.91
Rank	#20	Overall
	#14	Relational DBMS

Website

aws.amazon.com/dynamodb

www.datomic.com

www.claris.com/filemaker

www.intersystems.com/products/cache

Technical documentation

docs.aws.amazon.com/dynamodb

docs.datomic.com

www.claris.com/resources/documentation

docs.intersystems.com

Developer

Amazon

Cognitect

Claris

a subsidiary of Apple

InterSystems

Teradata

Initial release

2012

1983

1997

2005

Current release

1.0.6735, June 2023

19.4.1, November 2021

2018.1.4, May 2020

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

limited edition free

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

Java, Clojure

Server operating systems

hosted

All OS with a Java VM

iOS

client part only
Linux
OS X
Windows

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

Linux

Data scheme

schema-free

yes

depending on used data model

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

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

A http query request can return the data in XML format

yes

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

yes

via plugins

yes

APIs and other access methods

RESTful HTTP API

Filemaker WebDirect
JDBC
ODBC

.NET Client API
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Clojure
Java

PHP

C#
C++
Java

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

R packages

Triggers

yes

by integration with AWS Lambda

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

But extensive use of caching in the application peers

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

But extensive use of caching in the application peers

Source-replica replication, warm standby

since Version 14

Source-replica replication

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

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

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

User concepts

Access control

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

simple rights management via user accounts and connection to external directory services

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

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