DBMS > FileMaker vs. Google BigQuery vs. Microsoft SQL Server vs. SingleStore vs. WakandaDB

System Properties Comparison FileMaker vs. Google BigQuery vs. Microsoft SQL Server vs. SingleStore vs. WakandaDB

Editorial information provided by DB-Engines

Name

Description

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

Large scale data warehouse service with append-only tables

Microsofts flagship relational DBMS

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Relational DBMS

Object oriented DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	47.91
Rank	#20	Overall
	#14	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	5.38
Rank	#62	Overall
	#35	Relational DBMS

Score	0.10
Rank	#356	Overall
	#16	Object oriented DBMS

Website

www.claris.com/filemaker

cloud.google.com/bigquery

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

www.singlestore.com

wakanda.github.io

Technical documentation

www.claris.com/resources/documentation

cloud.google.com/bigquery/docs

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

docs.singlestore.com

wakanda.github.io/doc

Developer

Claris

a subsidiary of Apple

Google

Microsoft

SingleStore Inc.

Wakanda SAS

Initial release

1983

2010

1989

2013

2012

Current release

19.4.1, November 2021

SQL Server 2022, November 2022

8.5, January 2024

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

restricted free version is available

commercial

free developer edition available

Open Source

AGPLv3, extended commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C++, Go

C++, JavaScript

Server operating systems

iOS

client part only
Linux
OS X
Windows

hosted

Linux
Windows

Linux

64 bit version required

Linux
OS X
Windows

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

but no triggers and foreign keys

APIs and other access methods

Filemaker WebDirect
JDBC
ODBC

RESTful HTTP/JSON API

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

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

RESTful HTTP API

Supported programming languages

PHP

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

Bash
C
C#
Java
JavaScript (Node.js)
Python

JavaScript

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

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

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

Sharding

hash partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication, warm standby

since Version 14

yes, but depending on the SQL-Server Edition

Source-replica replication

stores two copies of each physical data partition on two separate nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

Fine grained access control via users, groups and roles

yes

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Market metrics

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Licensing and pricing models

F ree Tier and Enterprise Edition
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