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DBMS > Apache Kylin vs. Faircom DB vs. Solr

System Properties Comparison Apache Kylin vs. Faircom DB vs. Solr

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Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonFaircom DB infoformerly c-treeACE  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 stackNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.A widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSKey-value store
Relational DBMS
Search engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.20
Rank#159  Overall
#78  Relational DBMS
Score0.46
Rank#244  Overall
#38  Key-value stores
#116  Relational DBMS
Score51.06
Rank#20  Overall
#3  Search engines
Websitekylin.apache.orgwww.faircom.com/­products/­faircom-dblucene.apache.org/­solr
Technical documentationkylin.apache.org/­docslearn.faircomcorp.com/­developers/­documentation_directorylucene.apache.org/­solr/­resources.html
DeveloperApache Software Foundation, originally contributed from eBay IncFairCom CorporationApache Software Foundation
Initial release201519792006
Current release3.1.0, July 2020V12, November 20208.9.0, June 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoRestricted, free version availableOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaANSI C, C++Java
Server operating systemsLinuxAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesschema free, schema optional, schema required, partial schema,yes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyes 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.nonoyes
Secondary indexesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)yes, ANSI SQL with proprietary extensionsSolr Parallel SQL Interface
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
Java API
RESTful HTTP/JSON API
Supported programming languages.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
.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++Java plugins
Triggersyesyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Eventual Consistency
Foreign keys infoReferential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datatunable from ACID to Eventually Consistentoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesYes, tunable from durable to delayed durability to in-memoryyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesyes
More information provided by the system vendor
Apache KylinFaircom DB infoformerly c-treeACESolr
Specific characteristicsAchieve Hundreds of Thousands of Transactions Per Second on A Single Database Server...
» more
Competitive advantagesTop Features SQL Key-value store and navigational NoSQL API Indexed binary objects...
» more
Typical application scenariosReal-time transaction processing solutions leverage FairCom DB because its NoSQL...
» more
Key customersMicrosoft, UPS, Verizon, Motorola, Commvault, Thomson Reuters, ACI, BNY Mellon, Rockwell...
» more
Market metricsFrom banking and financial transactions, transportation, warehouse automation, package...
» more
Licensing and pricing modelsJust as the technical aspects of FairCom DB are flexible to meet operation requirements,...
» more

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More resources
Apache KylinFaircom DB infoformerly c-treeACESolr
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