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DBMS > Citus vs. DataFS vs. Google Cloud Firestore vs. LevelDB vs. Splice Machine

System Properties Comparison Citus vs. DataFS vs. Google Cloud Firestore vs. LevelDB vs. Splice Machine

Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonDataFS  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonLevelDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLAll data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.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.Embeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSObject oriented DBMSDocument storeKey-value storeRelational DBMS
Secondary database modelsDocument storeGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.13
Rank#117  Overall
#56  Relational DBMS
Score0.02
Rank#369  Overall
#18  Object oriented DBMS
Score6.63
Rank#54  Overall
#9  Document stores
Score2.33
Rank#111  Overall
#19  Key-value stores
Score0.54
Rank#244  Overall
#114  Relational DBMS
Websitewww.citusdata.comnewdatabase.comfirebase.google.com/­products/­firestoregithub.com/­google/­leveldbsplicemachine.com
Technical documentationdocs.citusdata.comdev.mobiland.com/­Overview.xspfirebase.google.com/­docs/­firestoregithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdsplicemachine.com/­how-it-works
DeveloperMobiland AGGoogleGoogleSplice Machine
Initial release20102018201720112014
Current release8.1, December 20181.1.263, October 20221.23, February 20213.1, March 2021
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialcommercialOpen Source infoBSDOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC++Java
Server operating systemsLinuxWindowshostedIllumos
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeyesClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)schema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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 indexesyesnoyesnoyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsnononoyes
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
.NET Client API
Proprietary client DLL
WinRT client
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C
C#
C++
VB.Net
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes, Firebase Rules & Cloud Functionsnoyes infoJava
Triggersyesno, except callback-events from server when changes happenedyes, with Cloud Functionsnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingProprietary Sharding systemShardingnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsMulti-source replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoUsing Cloud DataflownoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDyesnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes infowith automatic compression on writesyes
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-standardWindows-ProfileAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.noAccess rights for users, groups and roles according to SQL-standard

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More resources
CitusDataFSGoogle Cloud FirestoreLevelDBSplice Machine
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