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DBMS > Apache Kylin vs. Faircom EDGE vs. ObjectBox vs. Solr

System Properties Comparison Apache Kylin vs. Faircom EDGE vs. ObjectBox vs. Solr

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Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonObjectBox  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsExtremely fast embedded database for small devices, IoT and MobileA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSKey-value store
Relational DBMS
Object oriented DBMSSearch engine
Secondary database modelsTime Series DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.25
Rank#170  Overall
#77  Relational DBMS
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score1.29
Rank#166  Overall
#5  Object oriented DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websitekylin.apache.orgwww.faircom.com/­products/­faircom-edgeobjectbox.iosolr.apache.org
Technical documentationkylin.apache.org/­docsdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmldocs.objectbox.iosolr.apache.org/­resources.html
DeveloperApache Software Foundation, originally contributed from eBay IncFairCom CorporationObjectBox LimitedApache Software Foundation
Initial release2015197920172006
Current release3.1.0, July 2020V3, October 20209.6.1, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoRestricted, free version availableOpen Source infoApache License 2.0Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaANSI C, C++C and C++Java
Server operating systemsLinuxAndroid
Linux infoARM, x86
Raspbian
Windows
Android
iOS
Linux
macOS
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyesyes 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.noyesnoyes
Secondary indexesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)yes infoANSI SQL queriesnoSolr Parallel SQL Interface
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Proprietary native APIJava API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++noJava plugins
Triggersyesnoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesFile partitioning infoCustomizable business rules for partitioningnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoSynchronous and asynchronous realtime replication based on transaction logsonline/offline synchronization between client and serveryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Tunable Consistency
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infowhen using SQLyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyes
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.noyesnoyes
User concepts infoAccess controlFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.yesyes
More information provided by the system vendor
Apache KylinFaircom EDGE infoformerly c-treeEDGEObjectBoxSolr
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