DBMS > FileMaker vs. Graph Engine vs. Heroic vs. MonetDB vs. Snowflake

System Properties Comparison FileMaker vs. Graph Engine vs. Heroic vs. MonetDB vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

A relational database management system that stores data in columns

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	48.20
Rank	#20	Overall
	#14	Relational DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.claris.com/filemaker

www.graphengine.io

github.com/spotify/heroic

www.monetdb.org

www.snowflake.com

Technical documentation

www.claris.com/resources/documentation

www.graphengine.io/docs/manual

spotify.github.io/heroic

www.monetdb.org/Documentation

docs.snowflake.net/manuals/index.html

Developer

Claris

a subsidiary of Apple

Microsoft

Spotify

MonetDB BV

Snowflake Computing Inc.

Initial release

1983

2010

2014

2004

2014

Current release

19.4.1, November 2021

Dec2023 (11.49), December 2023

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

Apache 2.0

Open Source

Mozilla Public License 2.0

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

.NET and C

Java

Server operating systems

iOS

client part only
Linux
OS X
Windows

.NET

FreeBSD
Linux
OS X
Solaris
Windows

hosted

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

via plugins

yes

SQL 2003 with some extensions

yes

APIs and other access methods

Filemaker WebDirect
JDBC
ODBC

RESTful HTTP API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

PHP

C#
C++
F#
Visual Basic

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

yes, in SQL, C, R

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

Sharding via remote tables

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication, warm standby

since Version 14

yes

none

Source-replica replication available in experimental status

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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