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DBMS > Amazon DocumentDB vs. Datomic vs. Google Cloud Firestore vs. Kdb vs. SwayDB

System Properties Comparison Amazon DocumentDB vs. Datomic vs. Google Cloud Firestore vs. Kdb vs. SwayDB

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonDatomic  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonKdb  Xexclude from comparisonSwayDB  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceDatomic 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.High performance Time Series DBMSAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelDocument storeRelational DBMSDocument storeTime Series DBMS
Vector DBMS
Key-value store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score7.85
Rank#51  Overall
#8  Document stores
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Score0.00
Rank#382  Overall
#59  Key-value stores
Websiteaws.amazon.com/­documentdbwww.datomic.comfirebase.google.com/­products/­firestorekx.comswaydb.simer.au
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.datomic.comfirebase.google.com/­docs/­firestorecode.kx.com
DeveloperCognitectGoogleKx Systems, a division of First Derivatives plcSimer Plaha
Initial release2019201220172000 infokdb was released 2000, kdb+ in 20032018
Current release1.0.6735, June 20233.6, May 2018
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freecommercialcommercial infofree 32-bit versionOpen Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureqScala
Server operating systemshostedAll OS with a Java VMhostedLinux
OS X
Solaris
Windows
Data schemeschema-freeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyesno
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.nononoyesno
Secondary indexesyesyesyesyes infotable attribute 'grouped'no
SQL infoSupport of SQLnononoSQL-like query language (q)no
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)RESTful HTTP APIAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
Clojure
Java
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
Java
Kotlin
Scala
Server-side scripts infoStored proceduresnoyes infoTransaction Functionsyes, Firebase Rules & Cloud Functionsuser defined functionsno
TriggersnoBy using transaction functionsyes, with Cloud Functionsyes infowith viewsno
Partitioning methods infoMethods for storing different data on different nodesnonenone infoBut extensive use of caching in the application peersShardinghorizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasnone infoBut extensive use of caching in the application peersMulti-source replicationSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noUsing Cloud Dataflowno infosimilar paradigm used for internal processingno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDyesnoAtomic execution of operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes 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 developmentyesyes
User concepts infoAccess controlAccess rights for users and rolesnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.rights management via user accountsno
More information provided by the system vendor
Amazon DocumentDBDatomicGoogle Cloud FirestoreKdbSwayDB
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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More resources
Amazon DocumentDBDatomicGoogle Cloud FirestoreKdbSwayDB
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