DBMS > Faircom DB vs. FileMaker vs. Hawkular Metrics vs. Microsoft Access vs. SAP HANA

System Properties Comparison Faircom DB vs. FileMaker vs. Hawkular Metrics vs. Microsoft Access vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

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.

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.24
Rank	#311	Overall
	#44	Key-value stores
	#140	Relational DBMS

Score	49.73
Rank	#20	Overall
	#14	Relational DBMS

Score	0.04
Rank	#374	Overall
	#38	Time Series DBMS

Score	105.40
Rank	#11	Overall
	#8	Relational DBMS

Score	45.84
Rank	#22	Overall
	#16	Relational DBMS

Website

www.faircom.com/products/faircom-db

www.claris.com/filemaker

www.hawkular.org

www.microsoft.com/en-us/microsoft-365/access

www.sap.com/products/hana.html

Technical documentation

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

www.claris.com/resources/documentation

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

developer.microsoft.com/en-us/access

help.sap.com/hana

Developer

FairCom Corporation

Claris

a subsidiary of Apple

Community supported by Red Hat

Microsoft

SAP

Initial release

1979

1983

2014

1992

2010

Current release

V12, November 2020

19.4.1, November 2021

1902 (16.0.11328.20222), March 2019

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Open Source

Apache 2.0

commercial

Bundled with Microsoft Office

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

ANSI C, C++

Java

C++

Server operating systems

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

iOS

client part only
Linux
OS X
Windows

Linux
OS X
Windows

Windows

Not a real database server, but making use of DLLs

Appliance or cloud-service

Data scheme

schema free, schema optional, schema required, partial schema,

yes

schema-free

yes

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

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

Secondary indexes

yes

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

yes

via plugins

yes

but not compliant to any SQL standard

yes

APIs and other access methods

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

Filemaker WebDirect
JDBC
ODBC

HTTP REST

ADO.NET
DAO
ODBC
OLE DB

JDBC
ODBC

Supported programming languages

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

PHP

Go
Java
Python
Ruby

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

since Access 2010 using the ACE-engine

SQLScript, R

Triggers

yes

via Hawkular Alerting

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

none

Sharding

based on Cassandra

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

Source-replica replication, warm standby

since Version 14

selectable replication factor

based on Cassandra

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

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

tunable from ACID to Eventually Consistent

ACID

but no files for transaction logging

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Yes, tunable from durable to delayed durability to in-memory

yes

but no files for transaction logging

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 with additional protections for files

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

a simple user-level security was built in till version Access 2003

yes

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