DBMS > Drizzle vs. FileMaker vs. Google BigQuery vs. TimescaleDB

System Properties Comparison Drizzle vs. FileMaker vs. Google BigQuery vs. TimescaleDB

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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

Large scale data warehouse service with append-only tables

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Relational DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	48.20
Rank	#20	Overall
	#14	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

www.claris.com/filemaker

cloud.google.com/bigquery

www.timescale.com

Technical documentation

www.claris.com/resources/documentation

cloud.google.com/bigquery/docs

docs.timescale.com

Developer

Drizzle project, originally started by Brian Aker

Claris

a subsidiary of Apple

Google

Timescale

Initial release

2008

1983

2010

2017

Current release

7.2.4, September 2012

19.4.1, November 2021

2.15.0, May 2024

License

Commercial or Open Source

Open Source

GNU GPL

commercial

Open Source

Apache 2.0

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++

Server operating systems

FreeBSD
Linux
OS X

iOS

client part only
Linux
OS X
Windows

hosted

Linux
OS X
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

with proprietary extensions

yes

via plugins

yes

full PostgreSQL SQL syntax

APIs and other access methods

JDBC

Filemaker WebDirect
JDBC
ODBC

RESTful HTTP/JSON API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C
C++
Java
PHP

PHP

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication, warm standby

since Version 14

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

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

ACID

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

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.

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

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

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