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DBMS > Apache Impala vs. Apache Kylin vs. Faircom DB vs. OrigoDB vs. TerarkDB

System Properties Comparison Apache Impala vs. Apache Kylin vs. Faircom DB vs. OrigoDB vs. TerarkDB

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache Kylin  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonOrigoDB  Xexclude from comparisonTerarkDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA 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 fully ACID in-memory object graph databaseA 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 DBMSRelational DBMSKey-value store
Relational DBMS
Document store
Object oriented DBMS
Key-value store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.18
Rank#172  Overall
#79  Relational DBMS
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websiteimpala.apache.orgkylin.apache.orgwww.faircom.com/­products/­faircom-dborigodb.comgithub.com/­bytedance/­terarkdb
Technical documentationimpala.apache.org/­impala-docs.htmlkylin.apache.org/­docsdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlorigodb.com/­docsbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software Foundation, originally contributed from eBay IncFairCom CorporationRobert Friberg et alByteDance, originally Terark
Initial release2013201519792009 infounder the name LiveDB2016
Current release4.1.0, June 20223.1.0, July 2020V12, November 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0commercial infoRestricted, free version availableOpen Sourcecommercial 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 languageC++JavaANSI C, C++C#C++
Server operating systemsLinuxLinuxAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
Windows
Data schemeyesyesschema free, schema optional, schema required, partial schema,yesschema-free
Typing infopredefined data types such as float or dateyesyesyes, ANSI SQL Types, JSON, typed binary structuresUser defined using .NET types and collectionsno
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 infocan be achieved using .NETno
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsANSI SQL for queries (using Apache Calcite)yes, ANSI SQL with proprietary extensionsnono
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
.NET Client API
HTTP API
LINQ
C++ API
Java API
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
.NetC++
Java
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes info.Net, JavaScript, C/C++yesno
Triggersnoyesyes infoDomain Eventsno
Partitioning methods infoMethods for storing different data on different nodesShardingFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioninghorizontal partitioning infoclient side managed; servers are not synchronizednone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Foreign keys infoReferential integritynoyesdepending on modelno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanotunable from ACID to Eventually ConsistentACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesYes, tunable from durable to delayed durability to in-memoryyes infoWrite ahead logyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosFine grained access rights according to SQL-standard with additional protections for filesRole based authorizationno

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More resources
Apache ImpalaApache KylinFaircom DB infoformerly c-treeACEOrigoDBTerarkDB
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