DBMS > Datomic vs. FileMaker vs. Google BigQuery vs. Oracle Coherence

System Properties Comparison Datomic vs. FileMaker vs. Google BigQuery vs. Oracle Coherence

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Editorial information provided by DB-Engines

Name

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

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

Large scale data warehouse service with append-only tables

Oracles in-memory data grid solution

Primary database model

Relational DBMS

Key-value store

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

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	47.91
Rank	#20	Overall
	#14	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	1.97
Rank	#129	Overall
	#22	Key-value stores

Website

www.datomic.com

www.claris.com/filemaker

cloud.google.com/bigquery

www.oracle.com/java/coherence

Technical documentation

docs.datomic.com

www.claris.com/resources/documentation

cloud.google.com/bigquery/docs

docs.oracle.com/en/middleware/standalone/coherence

Developer

Cognitect

Claris

a subsidiary of Apple

Google

Oracle

Initial release

2012

1983

2010

2007

Current release

1.0.7075, December 2023

19.4.1, November 2021

14.1, August 2023

License

Commercial or Open Source

commercial

limited edition free

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Clojure

Java

Server operating systems

All OS with a Java VM

iOS

client part only
Linux
OS X
Windows

hosted

All OS with a Java VM

Data scheme

yes

schema-free

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

Secondary indexes

yes

SQL

Support of SQL

yes

via plugins

yes

APIs and other access methods

RESTful HTTP API

Filemaker WebDirect
JDBC
ODBC

RESTful HTTP/JSON API

JCache
JPA
RESTful HTTP API

Supported programming languages

Clojure
Java

PHP

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C++
Java

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

user defined functions

in JavaScript

Triggers

By using transaction functions

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

Source-replica replication, warm standby

since Version 14

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
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

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

optionally

In-memory capabilities

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

yes

recommended only for testing and development

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)

authentification to access the cache via certificates or http basic authentication

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