DBMS > Apache Druid vs. FileMaker vs. Google BigQuery vs. Informix

System Properties Comparison Apache Druid vs. FileMaker vs. Google BigQuery vs. Informix

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Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

Large scale data warehouse service with append-only tables

A secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things data

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Since Version 12.10 support for JSON/BSON datatypes compatible with MongoDB

Secondary database models

Document store
Spatial DBMS
Time Series DBMS

with Informix TimeSeries Extension

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	47.91
Rank	#20	Overall
	#14	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	17.12
Rank	#34	Overall
	#21	Relational DBMS

Website

druid.apache.org

www.claris.com/filemaker

cloud.google.com/bigquery

www.ibm.com/products/informix

Technical documentation

druid.apache.org/docs/latest/design

www.claris.com/resources/documentation

cloud.google.com/bigquery/docs

informix.hcldoc.com
www.ibm.com/support/knowledgecenter/SSGU8G/welcomeIfxServers.html

Developer

Apache Software Foundation and contributors

Claris

a subsidiary of Apple

Google

IBM, HCL Technologies

Effective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.

Initial release

2012

1983

2010

1984

Current release

29.0.1, April 2024

19.4.1, November 2021

14.10.FC5, November 2020

License

Commercial or Open Source

Open Source

Apache license v2

commercial

free developer edition available

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

Java

C, C++ and Java

Server operating systems

Linux
OS X
Unix

iOS

client part only
Linux
OS X
Windows

hosted

AIX
HP-UX
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-less columns are supported

yes

Typing

predefined data types such as float or date

yes

Since Version 12.10 support for JSON/BSON datatypes

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 for querying

yes

via plugins

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

Filemaker WebDirect
JDBC
ODBC

RESTful HTTP/JSON API

JDBC
JSON API

MongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

PHP

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Source-replica replication, warm standby

since Version 14

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

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

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

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)

Users with fine-grained authentication, authorization, and auditing controls

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