DBMS > Amazon DynamoDB vs. FileMaker vs. Hawkular Metrics vs. Interbase vs. TimescaleDB

System Properties Comparison Amazon DynamoDB vs. FileMaker vs. Hawkular Metrics vs. Interbase vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

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

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

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Light-weight proven RDBMS

originally from Borland

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Document store
Key-value store

Secondary database models

Relational DBMS

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

Score	77.57
Rank	#16	Overall
	#2	Document stores
	#2	Key-value stores

Score	49.73
Rank	#20	Overall
	#14	Relational DBMS

Score	0.04
Rank	#374	Overall
	#38	Time Series DBMS

Score	5.04
Rank	#71	Overall
	#39	Relational DBMS

Score	4.87
Rank	#74	Overall
	#4	Time Series DBMS

Website

aws.amazon.com/dynamodb

www.claris.com/filemaker

www.hawkular.org

www.embarcadero.com/products/interbase

www.timescale.com

Technical documentation

docs.aws.amazon.com/dynamodb

www.claris.com/resources/documentation

www.hawkular.org/hawkular-metrics/docs/user-guide

docs.embarcadero.com/products/interbase

docs.timescale.com

Developer

Amazon

Claris

a subsidiary of Apple

Community supported by Red Hat

Embarcadero

Timescale

Initial release

2012

1983

2014

1984

2017

Current release

19.4.1, November 2021

InterBase 2020, December 2019

2.13.0, November 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

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

Server operating systems

hosted

iOS

client part only
Linux
OS X
Windows

Linux
OS X
Windows

Android
iOS
Linux
OS X
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

export as XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

yes

via plugins

yes

full PostgreSQL SQL syntax

APIs and other access methods

RESTful HTTP API

Filemaker WebDirect
JDBC
ODBC

HTTP REST

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

PHP

Go
Java
Python
Ruby

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

Interbase procedure and trigger language

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

by integration with AWS Lambda

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on Cassandra

none

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication, warm standby

since Version 14

selectable replication factor

based on Cassandra

Interbase Change Views

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

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

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

Multiversion concurreny control

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)

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

fine grained access rights according to SQL-standard

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