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DBMS > AllegroGraph vs. Badger vs. Google Cloud Firestore vs. HEAVY.AI vs. HugeGraph

System Properties Comparison AllegroGraph vs. Badger vs. Google Cloud Firestore vs. HEAVY.AI vs. HugeGraph

Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonBadger  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonHugeGraph  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSAn 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 high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareA fast-speed and highly-scalable Graph DBMS
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Key-value storeDocument storeRelational DBMSGraph DBMS
Secondary database modelsSpatial DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.13
Rank#179  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#7  Vector DBMS
Score0.22
Rank#320  Overall
#47  Key-value stores
Score7.36
Rank#53  Overall
#9  Document stores
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score0.17
Rank#335  Overall
#31  Graph DBMS
Websiteallegrograph.comgithub.com/­dgraph-io/­badgerfirebase.google.com/­products/­firestoregithub.com/­heavyai/­heavydb
www.heavy.ai
github.com/­hugegraph
hugegraph.apache.org
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmlgodoc.org/­github.com/­dgraph-io/­badgerfirebase.google.com/­docs/­firestoredocs.heavy.aihugegraph.apache.org/­docs
DeveloperFranz Inc.DGraph LabsGoogleHEAVY.AI, Inc.Baidu
Initial release20042017201720162018
Current release8.0, December 20235.10, January 20220.9
License infoCommercial or Open Sourcecommercial infoLimited community edition freeOpen Source infoApache 2.0commercialOpen Source infoApache Version 2; enterprise edition availableOpen Source infoApache Version 2.0
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 languageGoC++ and CUDAJava
Server operating systemsLinux
OS X
Windows
BSD
Linux
OS X
Solaris
Windows
hostedLinuxLinux
macOS
Unix
Data schemeyes infoRDF schemasschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyesyes
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.no infobulk load of XML files possiblenononono
Secondary indexesyesnoyesnoyes infoalso supports composite index and range index
SQL infoSupport of SQLSPARQL is used as query languagenonoyesno
APIs and other access methodsRESTful HTTP API
SPARQL
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
Thrift
Vega
Java API
RESTful HTTP API
TinkerPop Gremlin
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
GoGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
All languages supporting JDBC/ODBC/Thrift
Python
Groovy
Java
Python
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispnoyes, Firebase Rules & Cloud Functionsnoasynchronous Gremlin script jobs
Triggersyesnoyes, with Cloud Functionsnono
Partitioning methods infoMethods for storing different data on different nodeswith FederationnoneShardingSharding infoRound robinyes infodepending on used storage backend, e.g. Cassandra and HBase
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
noneMulti-source replicationMulti-source replicationyes infodepending on used storage backend, e.g. Cassandra and HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoUsing Cloud Dataflownovia hugegraph-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationnoneImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonononoyes infoedges in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoyesnoACID
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.nonoyesyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.fine grained access rights according to SQL-standardUsers, roles and permissions
More information provided by the system vendor
AllegroGraphBadgerGoogle Cloud FirestoreHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022HugeGraph
Specific characteristicsKnowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more
Competitive advantagesAllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more
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