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DBMS > Apache Kylin vs. EJDB vs. Faircom DB vs. Spark SQL vs. TerarkDB

System Properties Comparison Apache Kylin vs. EJDB vs. Faircom DB vs. Spark SQL vs. TerarkDB

Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonEJDB  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonSpark SQL  Xexclude from comparisonTerarkDB  Xexclude from comparison
DescriptionA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Spark SQL is a component on top of 'Spark Core' for structured data processingA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelRelational DBMSDocument storeKey-value store
Relational DBMS
Relational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#172  Overall
#79  Relational DBMS
Score0.27
Rank#297  Overall
#44  Document stores
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitekylin.apache.orggithub.com/­Softmotions/­ejdbwww.faircom.com/­products/­faircom-dbspark.apache.org/­sqlgithub.com/­bytedance/­terarkdb
Technical documentationkylin.apache.org/­docsgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperApache Software Foundation, originally contributed from eBay IncSoftmotionsFairCom CorporationApache Software FoundationByteDance, originally Terark
Initial release20152012197920142016
Current release3.1.0, July 2020V12, November 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGPLv2commercial infoRestricted, free version availableOpen Source infoApache 2.0commercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCANSI C, C++ScalaC++
Server operating systemsLinuxserver-lessAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
OS X
Windows
Data schemeyesschema-freeschema free, schema optional, schema required, partial schema,yesschema-free
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, bool, date, object_idyes, ANSI SQL Types, JSON, typed binary structuresyesno
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.nononono
Secondary indexesyesnoyesnono
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)noyes, ANSI SQL with proprietary extensionsSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
in-process shared libraryADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
JDBC
ODBC
C++ API
Java API
Supported programming languagesActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
Java
Python
R
Scala
C++
Java
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++nono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Foreign keys infoReferential integrityno infotypically not needed, however similar functionality with collection joins possibleyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanotunable from ACID to Eventually Consistentnono
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/Write Lockingyesyesyes
Durability infoSupport for making data persistentyesyesYes, tunable from durable to delayed durability to in-memoryyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlnoFine grained access rights according to SQL-standard with additional protections for filesnono

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More resources
Apache KylinEJDBFaircom DB infoformerly c-treeACESpark SQLTerarkDB
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