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DBMS > Datomic vs. Firebase Realtime Database vs. GigaSpaces vs. Google Cloud Datastore

System Properties Comparison Datomic vs. Firebase Realtime Database vs. GigaSpaces vs. Google Cloud Datastore

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGigaSpaces  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform
Primary database modelRelational DBMSDocument storeDocument store
Object oriented DBMS infoValues are user defined objects
Document store
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.55
Rank#144  Overall
#67  Relational DBMS
Score13.60
Rank#39  Overall
#6  Document stores
Score0.91
Rank#197  Overall
#33  Document stores
#7  Object oriented DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Websitewww.datomic.comfirebase.google.com/­products/­realtime-databasewww.gigaspaces.comcloud.google.com/­datastore
Technical documentationdocs.datomic.comfirebase.google.com/­docs/­databasedocs.gigaspaces.com/­latest/­landing.htmlcloud.google.com/­datastore/­docs
DeveloperCognitectGoogle infoacquired by Google 2014Gigaspaces TechnologiesGoogle
Initial release2012201220002008
Current release1.0.7180, July 202415.5, September 2020
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen Source infoApache Version 2; Commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureJava, C++, .Net
Server operating systemsAll OS with a Java VMhostedLinux
macOS
Solaris
Windows
hosted
Data schemeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesyes, details here
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonono infoXML can be used for describing objects metadatano
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnonoSQL-99 for query and DML statementsSQL-like query language (GQL)
APIs and other access methodsRESTful HTTP APIAndroid
iOS
JavaScript API
RESTful HTTP API
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languagesClojure
Java
Java
JavaScript
Objective-C
.Net
C++
Java
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infoTransaction Functionslimited functionality with using 'rules'yesusing Google App Engine
TriggersBy using transaction functionsCallbacks are triggered when data changesyes, event driven architectureCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Multi-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoMap-Reduce pattern can be built with XAP task executorsyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.
Foreign keys infoReferential integritynononoyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyesno
User concepts infoAccess controlnoyes, based on authentication and database rulesRole-based access controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
DatomicFirebase Realtime DatabaseGigaSpacesGoogle Cloud Datastore
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