DBMS > Apache Drill vs. FileMaker vs. Google BigQuery vs. Realm vs. STSdb

System Properties Comparison Apache Drill vs. FileMaker vs. Google BigQuery vs. Realm vs. STSdb

Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

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

Large scale data warehouse service with append-only tables

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Document store
Relational DBMS

Relational DBMS

Document store

Key-value store

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

Score	2.02
Rank	#124	Overall
	#22	Document stores
	#59	Relational DBMS

Score	47.91
Rank	#20	Overall
	#14	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	7.41
Rank	#52	Overall
	#8	Document stores

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

drill.apache.org

www.claris.com/filemaker

cloud.google.com/bigquery

realm.io

github.com/STSSoft/STSdb4

Technical documentation

drill.apache.org/docs

www.claris.com/resources/documentation

cloud.google.com/bigquery/docs

realm.io/docs

Developer

Apache Software Foundation

Claris

a subsidiary of Apple

Google

Realm, acquired by MongoDB in May 2019

STS Soft SC

Initial release

2012

1983

2010

2014

2011

Current release

1.20.3, January 2023

19.4.1, November 2021

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

GPLv2, 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

Server operating systems

Linux
OS X
Windows

iOS

client part only
Linux
OS X
Windows

hosted

Android
Backend: server-less
iOS
Windows

Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

SQL SELECT statement is SQL:2003 compliant

yes

via plugins

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

Filemaker WebDirect
JDBC
ODBC

RESTful HTTP/JSON API

.NET Client API

Supported programming languages

C++

PHP

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
Java

with Android only
Objective-C
React Native
Swift

C#
Java

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions

in JavaScript

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication, warm standby

since Version 14

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Depending on the underlying data source

yes

In-Memory realm

User concepts

Access control

Depending on the underlying data source

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)

yes

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