DBMS > Datomic vs. Firebase Realtime Database vs. Hypertable

System Properties Comparison Datomic vs. Firebase Realtime Database vs. Hypertable

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Editorial information provided by DB-Engines
Name	Datomic  Xexclude from comparison	Firebase Realtime Database  Xexclude from comparison	Hypertable  Xexclude from comparison
			Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
Description	Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability	Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.	An open source BigTable implementation based on distributed file systems such as Hadoop
Primary database model	Relational DBMS	Document store	Wide column store
DB-Engines Ranking measures the popularity of database management systems Trend Chart	Score 1.73 Rank #135   Overall #67   Relational DBMS	Score 18.48 Rank #39   Overall #6   Document stores
Website	www.datomic.com	firebase.google.com/­products/­realtime-database
Technical documentation	docs.datomic.com	firebase.google.com/­docs/­database
Developer	Cognitect	Google acquired by Google 2014	Hypertable Inc.
Initial release	2012	2012	2009
Current release	1.0.6362, January 2022		0.9.8.11, March 2016
License Commercial or Open Source	commercial limited edition free	commercial	Open Source GNU version 3. Commercial license available
Cloud-based only Only available as a cloud service	no	yes	no
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Implementation language	Java, Clojure		C++
Server operating systems	All OS with a Java VM	hosted	Linux OS X Windows an inofficial Windows port is available
Data scheme	yes	schema-free	schema-free
Typing predefined data types such as float or date	yes	yes	no
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.	no	no
Secondary indexes	yes	yes	restricted only exact value or prefix value scans
SQL Support of SQL	no	no	no
APIs and other access methods	RESTful HTTP API	Android iOS JavaScript API RESTful HTTP API	C++ API Thrift
Supported programming languages	Clojure Java	Java JavaScript Objective-C	C++ Java Perl PHP Python Ruby
Server-side scripts Stored procedures	yes Transaction Functions	limited functionality with using 'rules'	no
Triggers	By using transaction functions	Callbacks are triggered when data changes	no
Partitioning methods Methods for storing different data on different nodes	none But extensive use of caching in the application peers		Sharding
Replication methods Methods for redundantly storing data on multiple nodes	none But extensive use of caching in the application peers		selectable replication factor on file system level
MapReduce Offers an API for user-defined Map/Reduce methods	no	no	yes
Consistency concepts Methods to ensure consistency in a distributed system	Immediate Consistency	Eventual Consistency if the client is offline Immediate Consistency if the client is online	Immediate Consistency
Foreign keys Referential integrity	no	no	no
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	ACID	yes	no
Concurrency Support for concurrent manipulation of data	yes	yes	yes
Durability Support for making data persistent	yes using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)	yes	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	no	yes, based on authentication and database rules	no
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	Datomic	Firebase Realtime Database	Hypertable
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