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

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

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonHugeGraph  Xexclude from comparisonSolr  Xexclude from comparison
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 widely used distributed, scalable search engine based on Apache Lucene
Primary database modelKey-value storeRelational DBMSDocument storeGraph DBMSSearch engine
Secondary database modelsDocument store
Spatial DBMS
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
Score41.02
Rank#24  Overall
#3  Search engines
Websitegithub.com/­dgraph-io/­badgerwww.postgresql.fastware.comfirebase.google.com/­products/­firestoregithub.com/­hugegraph
hugegraph.apache.org
solr.apache.org
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerwww.postgresql.fastware.com/­product-manualsfirebase.google.com/­docs/­firestorehugegraph.apache.org/­docssolr.apache.org/­resources.html
DeveloperDGraph LabsPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyGoogleBaiduApache Software Foundation
Initial release2017201720182006
Current releaseFujitsu Enterprise Postgres 14, January 20220.99.6.1, May 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2
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 languageGoCJavaJava
Server operating systemsBSD
Linux
OS X
Solaris
Windows
Linux
Windows
hostedLinux
macOS
Unix
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeyesschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or datenoyesyesyesyes infosupports customizable data types and automatic typing
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.nononoyes
Secondary indexesnoyesyesyes infoalso supports composite index and range indexyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnoyesnonoSolr Parallel SQL Interface
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
Java API
RESTful HTTP/JSON 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
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnouser defined functionsyes, Firebase Rules & Cloud Functionsasynchronous Gremlin script jobsJava plugins
Triggersnoyesyes, with Cloud Functionsnoyes infoUser configurable commands triggered on index changes
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 HBaseSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationMulti-source replicationyes infodepending on used storage backend, e.g. Cassandra and HBaseyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoUsing Cloud Dataflowvia hugegraph-sparkspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnoyes infoedges in graphno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDyesACIDoptimistic locking
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.noyesyes
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 permissionsyes

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BadgerFujitsu Enterprise PostgresGoogle Cloud FirestoreHugeGraphSolr
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