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DBMS > Citus vs. Firebase Realtime Database vs. Google Cloud Bigtable vs. HugeGraph

System Properties Comparison Citus vs. Firebase Realtime Database vs. Google Cloud Bigtable vs. HugeGraph

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHugeGraph  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A fast-speed and highly-scalable Graph DBMS
Primary database modelRelational DBMSDocument storeKey-value store
Wide column store
Graph DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score14.29
Rank#39  Overall
#6  Document stores
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.13
Rank#336  Overall
#32  Graph DBMS
Websitewww.citusdata.comfirebase.google.com/­products/­realtime-databasecloud.google.com/­bigtablegithub.com/­hugegraph
hugegraph.apache.org
Technical documentationdocs.citusdata.comfirebase.google.com/­docs/­databasecloud.google.com/­bigtable/­docshugegraph.apache.org/­docs
DeveloperGoogle infoacquired by Google 2014GoogleBaidu
Initial release2010201220152018
Current release8.1, December 20180.9
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJava
Server operating systemsLinuxhostedhostedLinux
macOS
Unix
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.yes infospecific XML type available, but no XML query functionalitynonono
Secondary indexesyesyesnoyes infoalso supports composite index and range index
SQL infoSupport of SQLyes infostandard, with numerous extensionsnonono
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Android
iOS
JavaScript API
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Java API
RESTful HTTP API
TinkerPop Gremlin
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
JavaScript
Objective-C
C#
C++
Go
Java
JavaScript (Node.js)
Python
Groovy
Java
Python
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.limited functionality with using 'rules'noasynchronous Gremlin script jobs
TriggersyesCallbacks are triggered when data changesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes infodepending on used storage backend, e.g. Cassandra and HBase
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsInternal replication in Colossus, and regional replication between two clusters in different zonesyes infodepending on used storage backend, e.g. Cassandra and HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesvia hugegraph-spark
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 (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Foreign keys infoReferential integrityyesnonoyes infoedges in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesAtomic single-row operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardyes, based on authentication and database rulesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users, roles and permissions

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More resources
CitusFirebase Realtime DatabaseGoogle Cloud BigtableHugeGraph
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