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DBMS > EJDB vs. Google Cloud Bigtable vs. Microsoft Azure AI Search vs. Solr

System Properties Comparison EJDB vs. Google Cloud Bigtable vs. Microsoft Azure AI Search vs. Solr

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Editorial information provided by DB-Engines
NameEJDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Search-as-a-service for web and mobile app developmentA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelDocument storeKey-value store
Wide column store
Search engineSearch engine
Secondary database modelsVector DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.27
Rank#297  Overall
#44  Document stores
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score5.59
Rank#63  Overall
#7  Search engines
Score42.91
Rank#24  Overall
#3  Search engines
Websitegithub.com/­Softmotions/­ejdbcloud.google.com/­bigtableazure.microsoft.com/­en-us/­services/­searchsolr.apache.org
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdcloud.google.com/­bigtable/­docslearn.microsoft.com/­en-us/­azure/­searchsolr.apache.org/­resources.html
DeveloperSoftmotionsGoogleMicrosoftApache Software Foundation
Initial release2012201520152006
Current releaseV19.5.0, February 2024
License infoCommercial or Open SourceOpen Source infoGPLv2commercialcommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJava
Server operating systemsserver-lesshostedhostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeschema-freeyesyes 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_idnoyesyes 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 indexesnonoyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnononoSolr Parallel SQL Interface
APIs and other access methodsin-process shared librarygRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
RESTful HTTP APIJava API
RESTful HTTP/JSON API
Supported programming languagesActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Python
C#
Java
JavaScript
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnononoJava plugins
Triggersnononoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneInternal replication in Colossus, and regional replication between two clusters in different zonesyes infoImplicit feature of the cloud serviceyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityno infotypically not needed, however similar functionality with collection joins possiblenonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsnooptimistic 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.nonoyes
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes infousing Azure authenticationyes

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More resources
EJDBGoogle Cloud BigtableMicrosoft Azure AI SearchSolr
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