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DBMS > AnzoGraph DB vs. Citus vs. Google Cloud Firestore vs. LevelDB vs. Splice Machine

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

Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonCitus  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonLevelDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLCloud 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 modelGraph DBMS
RDF store
Relational DBMSDocument storeKey-value storeRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#303  Overall
#25  Graph DBMS
#14  RDF stores
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score7.36
Rank#53  Overall
#9  Document stores
Score2.25
Rank#115  Overall
#19  Key-value stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitecambridgesemantics.com/­anzographwww.citusdata.comfirebase.google.com/­products/­firestoregithub.com/­google/­leveldbsplicemachine.com
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmdocs.citusdata.comfirebase.google.com/­docs/­firestoregithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdsplicemachine.com/­how-it-works
DeveloperCambridge SemanticsGoogleGoogleSplice Machine
Initial release20182010201720112014
Current release2.3, January 20218.1, December 20181.23, February 20213.1, March 2021
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoAGPL, commercial license also availablecommercialOpen 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++Java
Server operating systemsLinuxLinuxhostedIllumos
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeSchema-free and OWL/RDFS-schema supportyesschema-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.noyes infospecific XML type available, but no XML query functionalitynono
Secondary indexesnoyesyesnoyes
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.yes infostandard, with numerous extensionsnonoyes
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC++
Java
Python
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
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 and aggregatesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes, Firebase Rules & Cloud Functionsnoyes infoJava
Triggersnoyesyes, with Cloud Functionsnoyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingShardingnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-ClusterSource-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 methodsKerberos/HDFS data loadingnoUsing Cloud DataflownoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infonot needed in graphsyesnonoyes
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.yesnoyes
User concepts infoAccess controlAccess rights for users and rolesfine grained access rights according to SQL-standardAccess 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
AnzoGraph DBCitusGoogle Cloud FirestoreLevelDBSplice Machine
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