DBMS > atoti vs. Datomic vs. FileMaker vs. Heroic

System Properties Comparison atoti vs. Datomic vs. FileMaker vs. Heroic

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Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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.

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Primary database model

Object oriented DBMS

Relational DBMS

Time Series DBMS

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	48.20
Rank	#20	Overall
	#14	Relational DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Website

atoti.io

www.datomic.com

www.claris.com/filemaker

github.com/spotify/heroic

Technical documentation

docs.atoti.io

docs.datomic.com

www.claris.com/resources/documentation

spotify.github.io/heroic

Developer

ActiveViam

Cognitect

Claris

a subsidiary of Apple

Spotify

Initial release

2012

1983

2014

Current release

1.0.6735, June 2023

19.4.1, November 2021

License

Commercial or Open Source

commercial

free versions available

commercial

limited edition free

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Java, Clojure

Java

Server operating systems

All OS with a Java VM

iOS

client part only
Linux
OS X
Windows

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

via Elasticsearch

SQL

Support of SQL

Multidimensional Expressions (MDX)

yes

via plugins

APIs and other access methods

RESTful HTTP API

Filemaker WebDirect
JDBC
ODBC

HQL (Heroic Query Language, a JSON-based language)
HTTP API

Supported programming languages

Clojure
Java

PHP

Server-side scripts

Stored procedures

Python

yes

Transaction Functions

yes

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

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

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

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

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

yes

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

User concepts

Access control

simple rights management via user accounts and connection to external directory services

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