DBMS > FileMaker vs. HEAVY.AI vs. Microsoft SQL Server vs. mSQL vs. Vitess

System Properties Comparison FileMaker vs. HEAVY.AI vs. Microsoft SQL Server vs. mSQL vs. Vitess

Editorial information provided by DB-Engines

Name

Description

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

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Microsofts flagship relational DBMS

mSQL (Mini SQL) is a simple and lightweight RDBMS

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

www.claris.com/filemaker

github.com/heavyai/heavydb
www.heavy.ai

www.microsoft.com/en-us/sql-server

hughestech.com.au/products/msql

vitess.io

Technical documentation

www.claris.com/resources/documentation

docs.heavy.ai

learn.microsoft.com/en-US/sql/sql-server

vitess.io/docs

Developer

Claris

a subsidiary of Apple

HEAVY.AI, Inc.

Microsoft

Hughes Technologies

The Linux Foundation, PlanetScale

Initial release

1983

2016

1989

1994

2013

Current release

19.4.1, November 2021

5.10, January 2022

SQL Server 2022, November 2022

4.4, October 2021

15.0.2, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; enterprise edition available

commercial

restricted free version is available

commercial

free licenses can be provided

Open Source

Apache Version 2.0, commercial licenses available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++ and CUDA

C++

Server operating systems

iOS

client part only
Linux
OS X
Windows

Linux

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Docker
Linux
macOS

Data scheme

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

yes

Secondary indexes

yes

SQL

Support of SQL

yes

via plugins

yes

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

with proprietary extensions

APIs and other access methods

Filemaker WebDirect
JDBC
ODBC

JDBC
ODBC
Thrift
Vega

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

JDBC
ODBC

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

PHP

All languages supporting JDBC/ODBC/Thrift
Python

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C
C++
Delphi
Java
Perl
PHP
Tcl

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

tables can be distributed across several files (horizontal partitioning); sharding through federation

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication, warm standby

since Version 14

Multi-source replication

yes, but depending on the SQL-Server Edition

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

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

no user groups or roles

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