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DBMS > GridGain vs. Realm vs. Solr vs. Sqrrl vs. SWC-DB

System Properties Comparison GridGain vs. Realm vs. Solr vs. Sqrrl vs. SWC-DB

Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonRealm  Xexclude from comparisonSolr  Xexclude from comparisonSqrrl  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  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.
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteA 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 high performance, scalable Wide Column DBMS
Primary database modelKey-value store
Relational DBMS
Document storeSearch engineDocument store
Graph DBMS
Key-value store
Wide column store
Wide column store
Secondary database modelsSpatial DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score7.41
Rank#52  Overall
#8  Document stores
Score41.02
Rank#24  Overall
#3  Search engines
Score0.08
Rank#364  Overall
#13  Wide column stores
Websitewww.gridgain.comrealm.iosolr.apache.orgsqrrl.comgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationwww.gridgain.com/­docs/­index.htmlrealm.io/­docssolr.apache.org/­resources.html
DeveloperGridGain Systems, Inc.Realm, acquired by MongoDB in May 2019Apache Software FoundationAmazon infooriginally Sqrrl Data, Inc.Alex Kashirin
Initial release20072014200620122020
Current releaseGridGain 8.5.19.6.1, May 20240.5, April 2021
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoApache Version 2commercialOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetJavaJavaC++
Server operating systemsLinux
OS X
Solaris
Windows
Android
Backend: server-less
iOS
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)LinuxLinux
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 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.yesnoyesno
Secondary indexesyesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLnoSolr Parallel SQL InterfacenoSQL-like query language
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Java API
RESTful HTTP/JSON API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Proprietary protocol
Thrift
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
.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
C++
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)no inforuns within the applications so server-side scripts are unnecessaryJava pluginsnono
Triggersyes (cache interceptors and events)yes 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 nodesyes (replicated cache)noneyesselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)nospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceyesno
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.Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDoptimistic lockingAtomic updates per row, document, or graph entity
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.yesyes infoIn-Memory realmyesno
User concepts infoAccess controlSecurity Hooks for custom implementationsyesyesCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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