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DBMS > Datomic vs. Google Cloud Firestore vs. Quasardb vs. Riak KV

System Properties Comparison Datomic vs. Google Cloud Firestore vs. Quasardb vs. Riak KV

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonQuasardb  Xexclude from comparisonRiak KV  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityCloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.Distributed, high-performance timeseries databaseDistributed, fault tolerant key-value store
Primary database modelRelational DBMSDocument storeTime Series DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexes
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score7.85
Rank#51  Overall
#8  Document stores
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Websitewww.datomic.comfirebase.google.com/­products/­firestorequasar.ai
Technical documentationdocs.datomic.comfirebase.google.com/­docs/­firestoredoc.quasar.ai/­masterwww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperCognitectGooglequasardbOpenSource, formerly Basho Technologies
Initial release2012201720092009
Current release1.0.6735, June 20233.14.1, January 20243.2.0, December 2022
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC++Erlang
Server operating systemsAll OS with a Java VMhostedBSD
Linux
OS X
Windows
Linux
OS X
Data schemeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes infointeger and binaryno
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.nononono
Secondary indexesyesyesyes infowith tagsrestricted
SQL infoSupport of SQLnonoSQL-like query languageno
APIs and other access methodsRESTful HTTP APIAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
HTTP APIHTTP API
Native Erlang Interface
Supported programming languagesClojure
Java
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresyes infoTransaction Functionsyes, Firebase Rules & Cloud FunctionsnoErlang
TriggersBy using transaction functionsyes, with Cloud Functionsnoyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingSharding infoconsistent hashingSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replicationSource-replica replication with selectable replication factorselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoUsing Cloud Dataflowwith Hadoop integrationyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACIDno
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)yesyes infoby using LevelDByes
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 developmentyes infoTransient mode
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.Cryptographically strong user authentication and audit trailyes, using Riak Security

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More resources
DatomicGoogle Cloud FirestoreQuasardbRiak KV
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