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DBMS > Badger vs. Fujitsu Enterprise Postgres vs. Google Cloud Firestore vs. HugeGraph vs. IRONdb

System Properties Comparison Badger vs. Fujitsu Enterprise Postgres vs. Google Cloud Firestore vs. HugeGraph vs. IRONdb

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonHugeGraph  Xexclude from comparisonIRONdb  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.Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.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 simplicity
Primary database modelKey-value storeRelational DBMSDocument storeGraph DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score0.37
Rank#278  Overall
#128  Relational DBMS
Score7.36
Rank#53  Overall
#9  Document stores
Score0.17
Rank#335  Overall
#31  Graph DBMS
Websitegithub.com/­dgraph-io/­badgerwww.postgresql.fastware.comfirebase.google.com/­products/­firestoregithub.com/­hugegraph
hugegraph.apache.org
www.circonus.com/solutions/time-series-database/
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerwww.postgresql.fastware.com/­product-manualsfirebase.google.com/­docs/­firestorehugegraph.apache.org/­docsdocs.circonus.com/irondb/category/getting-started
DeveloperDGraph LabsPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyGoogleBaiduCirconus LLC.
Initial release2017201720182017
Current releaseFujitsu Enterprise Postgres 14, January 20220.9V0.10.20, January 2018
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialOpen Source infoApache Version 2.0commercial
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 languageGoCJavaC and C++
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Linux
Windows
hostedLinux
macOS
Unix
Linux
Data schemeschema-freeyesschema-freeyesschema-free
Typing infopredefined data types such as float or datenoyesyesyesyes infotext, numeric, histograms
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 indexno
SQL infoSupport of SQLnoyesnonoSQL-like query language (Circonus Analytics Query Language: CAQL)
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Java API
RESTful HTTP API
TinkerPop Gremlin
HTTP API
Supported programming languagesGo.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Go
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
Server-side scripts infoStored proceduresnouser defined functionsyes, Firebase Rules & Cloud Functionsasynchronous Gremlin script jobsyes, in Lua
Triggersnoyesyes, with Cloud Functionsnono
Partitioning methods infoMethods for storing different data on different nodesnonepartitioning by range, list and by hashShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseAutomatic, metric affinity per node
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationMulti-source replicationyes infodepending on used storage backend, e.g. Cassandra and HBaseconfigurable replication factor, datacenter aware
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoUsing Cloud Dataflowvia hugegraph-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integritynoyesnoyes infoedges in graphno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDyesACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyesyes
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.noyesno
User concepts infoAccess controlnofine 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.Users, roles and permissionsno
More information provided by the system vendor
BadgerFujitsu Enterprise PostgresGoogle Cloud FirestoreHugeGraphIRONdb
Specific characteristics100% compatible with community PostgreSQL
» more
Competitive advantagesBuilt-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more
Typical application scenariosTransactional payments applications, reporting and mixed workloads.
» more
Market metricsOver 30 years experience in database technology. Over 20 years in Postgres development...
» more
Licensing and pricing modelsCore based licensing
» more

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More resources
BadgerFujitsu Enterprise PostgresGoogle Cloud FirestoreHugeGraphIRONdb
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