DBMS > FileMaker vs. GigaSpaces vs. Microsoft Access vs. SAP HANA vs. Splice Machine

System Properties Comparison FileMaker vs. GigaSpaces vs. Microsoft Access vs. SAP HANA vs. Splice Machine

Editorial information provided by DB-Engines

Name

Description

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

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

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

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Secondary database models

Graph DBMS
Search engine

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	47.91
Rank	#20	Overall
	#14	Relational DBMS

Score	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Website

www.claris.com/filemaker

www.gigaspaces.com

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

www.sap.com/products/hana.html

splicemachine.com

Technical documentation

www.claris.com/resources/documentation

docs.gigaspaces.com/latest/landing.html

developer.microsoft.com/en-us/access

help.sap.com/hana

splicemachine.com/how-it-works

Developer

Claris

a subsidiary of Apple

Gigaspaces Technologies

Microsoft

SAP

Splice Machine

Initial release

1983

2000

1992

2010

2014

Current release

19.4.1, November 2021

15.5, September 2020

1902 (16.0.11328.20222), March 2019

2.0 SPS07 (April 4, 2023), April 2023

3.1, March 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; Commercial licenses available

commercial

Bundled with Microsoft Office

commercial

Open Source

AGPL 3.0, commercial license available

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

Java, C++, .Net

C++

Java

Server operating systems

iOS

client part only
Linux
OS X
Windows

Linux
macOS
Solaris
Windows

Windows

Not a real database server, but making use of DLLs

Appliance or cloud-service

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

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

XML can be used for describing objects metadata

Secondary indexes

yes

SQL

Support of SQL

yes

via plugins

SQL-99 for query and DML statements

yes

but not compliant to any SQL standard

yes

APIs and other access methods

Filemaker WebDirect
JDBC
ODBC

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

ADO.NET
DAO
ODBC
OLE DB

JDBC
ODBC

JDBC
Native Spark Datasource
ODBC

Supported programming languages

PHP

.Net
C++
Java
Python
Scala

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

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

yes

since Access 2010 using the ACE-engine

SQLScript, R

yes

Java

Triggers

yes

yes, event driven architecture

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

yes

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication, warm standby

since Version 14

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

none

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

but no files for transaction logging

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

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

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

Role-based access control

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

yes

Access rights for users, groups and roles according to SQL-standard

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