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DBMS > EJDB vs. EsgynDB vs. Google Cloud Firestore vs. Solr

System Properties Comparison EJDB vs. EsgynDB vs. Google Cloud Firestore vs. Solr

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Editorial information provided by DB-Engines
NameEJDB  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Enterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionCloud 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 widely used distributed, scalable search engine based on Apache Lucene
Primary database modelDocument storeRelational DBMSDocument storeSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.27
Rank#297  Overall
#44  Document stores
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score7.85
Rank#51  Overall
#8  Document stores
Score42.91
Rank#24  Overall
#3  Search engines
Websitegithub.com/­Softmotions/­ejdbwww.esgyn.cnfirebase.google.com/­products/­firestoresolr.apache.org
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdfirebase.google.com/­docs/­firestoresolr.apache.org/­resources.html
DeveloperSoftmotionsEsgynGoogleApache Software Foundation
Initial release2012201520172006
Current release9.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoGPLv2commercialcommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC++, JavaJava
Server operating systemsserver-lessLinuxhostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyes infostring, integer, double, bool, date, object_idyesyesyes 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.nonoyes
Secondary indexesnoyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnoyesnoSolr Parallel SQL Interface
APIs and other access methodsin-process shared libraryADO.NET
JDBC
ODBC
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Supported programming languagesActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
All languages supporting JDBC/ODBC/ADO.NetGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnoJava Stored Proceduresyes, Firebase Rules & Cloud FunctionsJava plugins
Triggersnonoyes, with Cloud Functionsyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication between multi datacentersMulti-source replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesUsing Cloud Dataflowspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityno infotypically not needed, however similar functionality with collection joins possibleyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDyesoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayes infoRead/Write Lockingyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
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.yes

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More resources
EJDBEsgynDBGoogle Cloud FirestoreSolr
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