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DBMS > EsgynDB vs. Realm vs. Solr vs. Sqrrl vs. ToroDB

System Properties Comparison EsgynDB vs. Realm vs. Solr vs. Sqrrl vs. ToroDB

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonRealm  Xexclude from comparisonSolr  Xexclude from comparisonSqrrl  Xexclude from comparisonToroDB  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataA widely used distributed, scalable search engine based on Apache LuceneAdaptable, secure NoSQL built on Apache AccumuloA MongoDB-compatible JSON document store, built on top of PostgreSQL
Primary database modelRelational DBMSDocument storeSearch engineDocument store
Graph DBMS
Key-value store
Wide column store
Document store
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score7.41
Rank#52  Overall
#8  Document stores
Score41.02
Rank#24  Overall
#3  Search engines
Websitewww.esgyn.cnrealm.iosolr.apache.orgsqrrl.comgithub.com/­torodb/­server
Technical documentationrealm.io/­docssolr.apache.org/­resources.html
DeveloperEsgynRealm, acquired by MongoDB in May 2019Apache Software FoundationAmazon infooriginally Sqrrl Data, Inc.8Kdata
Initial release20152014200620122016
Current release9.6.1, May 2024
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoApache Version 2commercialOpen Source infoAGPL-V3
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaJavaJavaJava
Server operating systemsLinuxAndroid
Backend: server-less
iOS
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)LinuxAll OS with a Java 7 VM
Data schemeyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typingyesyes infostring, integer, double, boolean, date, object_id
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 indexesyesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLyesnoSolr Parallel SQL Interfaceno
APIs and other access methodsADO.NET
JDBC
ODBC
Java API
RESTful HTTP/JSON API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
Java infowith Android only
Objective-C
React Native
Swift
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresJava Stored Proceduresno inforuns within the applications so server-side scripts are unnecessaryJava pluginsno
Triggersnoyes infoChange Listenersyes infoUser configurable commands triggered on index changesnono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingSharding infomaking use of HadoopSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersnoneyesselectable replication factor infomaking use of HadoopSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDoptimistic lockingAtomic updates per row, document, or graph entityno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noyes infoIn-Memory realmyes
User concepts infoAccess controlfine grained access rights according to SQL-standardyesyesCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)Access rights for users and roles

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More resources
EsgynDBRealmSolrSqrrlToroDB
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