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DBMS > Badger vs. Google Cloud Firestore vs. HugeGraph vs. IRONdb vs. Splice Machine

System Properties Comparison Badger vs. Google Cloud Firestore vs. HugeGraph vs. IRONdb vs. Splice Machine

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonHugeGraph  Xexclude from comparisonIRONdb  Xexclude from comparisonSplice Machine  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAn 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 fast-speed and highly-scalable Graph DBMSA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value storeDocument storeGraph DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value 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/­firestoregithub.com/­hugegraph
hugegraph.apache.org
www.circonus.com/solutions/time-series-database/splicemachine.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerfirebase.google.com/­docs/­firestorehugegraph.apache.org/­docsdocs.circonus.com/irondb/category/getting-startedsplicemachine.com/­how-it-works
DeveloperDGraph LabsGoogleBaiduCirconus LLC.Splice Machine
Initial release20172017201820172014
Current release0.9V0.10.20, January 20183.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache Version 2.0commercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJavaC and C++Java
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedLinux
macOS
Unix
LinuxLinux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or datenoyesyesyes infotext, numeric, histogramsyes
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 indexesnoyesyes infoalso supports composite index and range indexnoyes
SQL infoSupport of SQLnononoSQL-like query language (Circonus Analytics Query Language: CAQL)yes
APIs and other access methodsAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Java API
RESTful HTTP API
TinkerPop Gremlin
HTTP APIJDBC
Native Spark Datasource
ODBC
Supported programming languagesGoGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
Groovy
Java
Python
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyes, Firebase Rules & Cloud Functionsasynchronous Gremlin script jobsyes, in Luayes infoJava
Triggersnoyes, with Cloud Functionsnonoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseAutomatic, metric affinity per nodeShared 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 HBaseconfigurable replication factor, datacenter awareMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoUsing Cloud Dataflowvia hugegraph-sparknoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyEventual ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate Consistency
Foreign keys infoReferential integritynonoyes infoedges in graphnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACIDnoACID
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.noyesnoyes
User concepts infoAccess controlnoAccess 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 permissionsnoAccess rights for users, groups and roles according to SQL-standard

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More resources
BadgerGoogle Cloud FirestoreHugeGraphIRONdbSplice Machine
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