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DBMS > Amazon DocumentDB vs. EsgynDB vs. RavenDB vs. Solr vs. Yaacomo

System Properties Comparison Amazon DocumentDB vs. EsgynDB vs. RavenDB vs. Solr vs. Yaacomo

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonEsgynDB  Xexclude from comparisonRavenDB  Xexclude from comparisonSolr  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseA 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 modelDocument storeRelational DBMSDocument storeSearch engineRelational DBMS
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score2.84
Rank#101  Overall
#18  Document stores
Score41.02
Rank#24  Overall
#3  Search engines
Websiteaws.amazon.com/­documentdbwww.esgyn.cnravendb.netsolr.apache.orgyaacomo.com
Technical documentationaws.amazon.com/­documentdb/­resourcesravendb.net/­docssolr.apache.org/­resources.html
DeveloperEsgynHibernating RhinosApache Software FoundationQ2WEB GmbH
Initial release20192015201020062009
Current release5.4, July 20229.6.1, May 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoAGPL version 3, commercial license availableOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaC#Java
Server operating systemshostedLinuxLinux
macOS
Raspberry Pi
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Android
Linux
Windows
Data schemeschema-freeyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyesnoyes 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.nonoyesno
Secondary indexesyesyesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLnoyesSQL-like query language (RQL)Solr Parallel SQL Interfaceyes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)ADO.NET
JDBC
ODBC
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Java API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
All languages supporting JDBC/ODBC/ADO.Net.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.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 ProceduresyesJava plugins
Triggersnonoyesyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasMulti-source replication between multi datacentersMulti-source replicationyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yesyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACID, Cluster-wide transaction availableoptimistic 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.noyesyes
User concepts infoAccess controlAccess rights for users and rolesfine grained access rights according to SQL-standardAuthorization levels configured per client per databaseyesfine grained access rights according to SQL-standard

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More resources
Amazon DocumentDBEsgynDBRavenDBSolrYaacomo
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