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DBMS > Apache Kylin vs. Faircom EDGE vs. Microsoft Access vs. Splice Machine

System Properties Comparison Apache Kylin vs. Faircom EDGE vs. Microsoft Access vs. Splice Machine

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Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonSplice Machine  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 environmentsMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#172  Overall
#79  Relational DBMS
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitekylin.apache.orgwww.faircom.com/­products/­faircom-edgewww.microsoft.com/­en-us/­microsoft-365/­accesssplicemachine.com
Technical documentationkylin.apache.org/­docsdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmldeveloper.microsoft.com/­en-us/­accesssplicemachine.com/­how-it-works
DeveloperApache Software Foundation, originally contributed from eBay IncFairCom CorporationMicrosoftSplice Machine
Initial release2015197919922014
Current release3.1.0, July 2020V3, October 20201902 (16.0.11328.20222), March 20193.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoRestricted, free version availablecommercial infoBundled with Microsoft OfficeOpen Source infoAGPL 3.0, commercial license available
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++Java
Server operating systemsLinuxAndroid
Linux infoARM, x86
Raspbian
Windows
Windows infoNot a real database server, but making use of DLLsLinux
OS X
Solaris
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyesyes
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.noyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)yes infoANSI SQL queriesyes infobut not compliant to any SQL standardyes
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
ADO.NET
DAO
ODBC
OLE DB
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++yes infosince Access 2010 using the ACE-engineyes infoJava
Triggersyesyes infosince Access 2010 using the ACE-engineyes
Partitioning methods infoMethods for storing different data on different nodesFile partitioning infoCustomizable business rules for partitioningnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoSynchronous and asynchronous realtime replication based on transaction logsnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infowhen using SQLyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infobut no files for transaction loggingACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infobut no files for transaction loggingyes
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 user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.no infoa simple user-level security was built in till version Access 2003Access rights for users, groups and roles according to SQL-standard

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More resources
Apache KylinFaircom EDGE infoformerly c-treeEDGEMicrosoft AccessSplice Machine
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