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DBMS > Amazon DocumentDB vs. Badger vs. Google Cloud Firestore vs. HugeGraph vs. IRONdb

System Properties Comparison Amazon DocumentDB vs. Badger vs. Google Cloud Firestore vs. HugeGraph vs. IRONdb

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonBadger  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonHugeGraph  Xexclude from comparisonIRONdb  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Cloud 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.A fast-speed and highly-scalable Graph DBMSA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity
Primary database modelDocument storeKey-value storeDocument storeGraph DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score0.22
Rank#320  Overall
#47  Key-value stores
Score7.36
Rank#53  Overall
#9  Document stores
Score0.17
Rank#335  Overall
#31  Graph DBMS
Websiteaws.amazon.com/­documentdbgithub.com/­dgraph-io/­badgerfirebase.google.com/­products/­firestoregithub.com/­hugegraph
hugegraph.apache.org
www.circonus.com/solutions/time-series-database/
Technical documentationaws.amazon.com/­documentdb/­resourcesgodoc.org/­github.com/­dgraph-io/­badgerfirebase.google.com/­docs/­firestorehugegraph.apache.org/­docsdocs.circonus.com/irondb/category/getting-started
DeveloperDGraph LabsGoogleBaiduCirconus LLC.
Initial release20192017201720182017
Current release0.9V0.10.20, January 2018
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen Source infoApache Version 2.0commercial
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 languageGoJavaC and C++
Server operating systemshostedBSD
Linux
OS X
Solaris
Windows
hostedLinux
macOS
Unix
Linux
Data schemeschema-freeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesnoyesyesyes infotext, numeric, histograms
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.nonononono
Secondary indexesyesnoyesyes infoalso supports composite index and range indexno
SQL infoSupport of SQLnonononoSQL-like query language (Circonus Analytics Query Language: CAQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Java API
RESTful HTTP API
TinkerPop Gremlin
HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
GoGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
Groovy
Java
Python
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Server-side scripts infoStored proceduresnonoyes, Firebase Rules & Cloud Functionsasynchronous Gremlin script jobsyes, in Lua
Triggersnonoyes, with Cloud Functionsnono
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseAutomatic, metric affinity per node
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasnoneMulti-source replicationyes infodepending on used storage backend, e.g. Cassandra and HBaseconfigurable replication factor, datacenter aware
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noUsing Cloud Dataflowvia hugegraph-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate ConsistencyEventual ConsistencyImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonoyes infoedges in graphno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnoyesACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
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.Users, roles and permissionsno

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More resources
Amazon DocumentDBBadgerGoogle Cloud FirestoreHugeGraphIRONdb
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