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DBMS > Apache Kylin vs. Faircom DB vs. HugeGraph vs. Impala

System Properties Comparison Apache Kylin vs. Faircom DB vs. HugeGraph vs. Impala

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Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonHugeGraph  Xexclude from comparisonImpala  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 fast-speed and highly-scalable Graph DBMSAnalytic DBMS for Hadoop
Primary database modelRelational DBMSKey-value store
Relational DBMS
Graph DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.36
Rank#145  Overall
#71  Relational DBMS
Score0.44
Rank#246  Overall
#38  Key-value stores
#117  Relational DBMS
Score0.12
Rank#307  Overall
#28  Graph DBMS
Score18.68
Rank#38  Overall
#23  Relational DBMS
Websitekylin.apache.orgwww.faircom.com/­products/­faircom-dbgithub.com/­hugegraphwww.cloudera.com/­products/­open-source/­apache-hadoop/­impala.html
Technical documentationkylin.apache.org/­docslearn.faircomcorp.com/­developers/­documentation_directoryhugegraph.github.io/­hugegraph-docdocs.cloudera.com/­documentation/­enterprise/­latest/­topics/­impala.html
DeveloperApache Software Foundation, originally contributed from eBay IncFairCom CorporationBaiduCloudera
Initial release2015197920182013
Current release3.1.0, July 2020V12, November 20200.93.4.0, April 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoRestricted, free version availableOpen Source infoApache Version 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++JavaC++
Server operating systemsLinuxAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
macOS
Unix
Linux
Data schemeyesschema free, schema optional, schema required, partial schema,yesyes
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyesyes
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 indexesyesyesyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)yes, ANSI SQL with proprietary extensionsnoSQL-like DML and DDL statements
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 API
TinkerPop Gremlin
JDBC
ODBC
Supported programming languages.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
Groovy
Java
Python
All languages supporting JDBC/ODBC
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++asynchronous Gremlin script jobsyes infouser defined functions and integration of map-reduce
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding
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 infodepending on used storage backend, e.g. Cassandra and HBaseselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnovia hugegraph-sparkyes infoquery execution via MapReduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesyes infoedges in graphno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datatunable from ACID to Eventually ConsistentACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesYes, 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.noyesyesno
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesUsers, roles and permissionsAccess rights for users, groups and roles infobased on Apache Sentry and Kerberos
More information provided by the system vendor
Apache KylinFaircom DB infoformerly c-treeACEHugeGraphImpala
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-treeACEHugeGraphImpala
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