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DBMS > Badger vs. Firebase Realtime Database vs. Google Cloud Firestore vs. HugeGraph vs. Splice Machine

System Properties Comparison Badger vs. Firebase Realtime Database vs. Google Cloud Firestore vs. HugeGraph vs. Splice Machine

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonHugeGraph  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.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 DBMSOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value storeDocument storeDocument storeGraph DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score13.64
Rank#39  Overall
#6  Document stores
Score7.36
Rank#53  Overall
#9  Document stores
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerfirebase.google.com/­products/­realtime-databasefirebase.google.com/­products/­firestoregithub.com/­hugegraph
hugegraph.apache.org
splicemachine.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerfirebase.google.com/­docs/­databasefirebase.google.com/­docs/­firestorehugegraph.apache.org/­docssplicemachine.com/­how-it-works
DeveloperDGraph LabsGoogle infoacquired by Google 2014GoogleBaiduSplice Machine
Initial release20172012201720182014
Current release0.93.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialOpen Source infoApache Version 2.0Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoJavaJava
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedhostedLinux
macOS
Unix
Linux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datenoyesyesyesyes
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.nononono
Secondary indexesnoyesyesyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLnonononoyes
APIs and other access methodsAndroid
iOS
JavaScript API
RESTful HTTP API
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Java API
RESTful HTTP API
TinkerPop Gremlin
JDBC
Native Spark Datasource
ODBC
Supported programming languagesGoJava
JavaScript
Objective-C
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
Groovy
Java
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnolimited functionality with using 'rules'yes, Firebase Rules & Cloud Functionsasynchronous Gremlin script jobsyes infoJava
TriggersnoCallbacks are triggered when data changesyes, with Cloud Functionsnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replicationyes infodepending on used storage backend, e.g. Cassandra and HBaseMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoUsing Cloud Dataflowvia hugegraph-sparkYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes infoedges in graphyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesyesACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
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.noyesyes
User concepts infoAccess controlnoyes, based on authentication and database rulesAccess 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 permissionsAccess rights for users, groups and roles according to SQL-standard

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More resources
BadgerFirebase Realtime DatabaseGoogle Cloud FirestoreHugeGraphSplice Machine
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