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DBMS > EsgynDB vs. Google Cloud Datastore vs. Microsoft Azure AI Search vs. Solr vs. Yaacomo

System Properties Comparison EsgynDB vs. Google Cloud Datastore vs. Microsoft Azure AI Search vs. Solr vs. Yaacomo

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSolr  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformSearch-as-a-service for web and mobile app developmentA widely used distributed, scalable search engine based on Apache LuceneOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSDocument storeSearch engineSearch engineRelational DBMS
Secondary database modelsVector DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score5.52
Rank#59  Overall
#6  Search engines
Score41.02
Rank#24  Overall
#3  Search engines
Websitewww.esgyn.cncloud.google.com/­datastoreazure.microsoft.com/­en-us/­services/­searchsolr.apache.orgyaacomo.com
Technical documentationcloud.google.com/­datastore/­docslearn.microsoft.com/­en-us/­azure/­searchsolr.apache.org/­resources.html
DeveloperEsgynGoogleMicrosoftApache Software FoundationQ2WEB GmbH
Initial release20152008201520062009
Current releaseV19.6.1, May 2024
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaJava
Server operating systemsLinuxhostedhostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Android
Linux
Windows
Data schemeyesschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyes infosupports customizable data types and automatic typingyes
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.nononoyesno
Secondary indexesyesyesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLyesSQL-like query language (GQL)noSolr Parallel SQL Interfaceyes
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP APIJava API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
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 proceduresJava Stored Proceduresusing Google App EnginenoJava plugins
TriggersnoCallbacks using the Google Apps Enginenoyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersMulti-source replication using Paxosyes infoImplicit feature of the cloud serviceyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud Dataflownospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnooptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.nononoyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes infousing Azure authenticationyesfine grained access rights according to SQL-standard

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More resources
EsgynDBGoogle Cloud DatastoreMicrosoft Azure AI SearchSolrYaacomo
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