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DBMS > Apache Kylin vs. Faircom DB vs. FatDB vs. FeatureBase vs. Microsoft Azure Synapse Analytics

System Properties Comparison Apache Kylin vs. Faircom DB vs. FatDB vs. FeatureBase vs. Microsoft Azure Synapse Analytics

Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonFatDB  Xexclude from comparisonFeatureBase  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
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 .NET NoSQL DBMS that can integrate with and extend SQL Server.Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server
Primary database modelRelational DBMSKey-value store
Relational DBMS
Document store
Key-value store
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.14
Rank#171  Overall
#77  Relational DBMS
Score0.18
Rank#314  Overall
#45  Key-value stores
#141  Relational DBMS
Score0.23
Rank#296  Overall
#134  Relational DBMS
Score18.98
Rank#31  Overall
#19  Relational DBMS
Websitekylin.apache.orgwww.faircom.com/­products/­faircom-dbwww.featurebase.comazure.microsoft.com/­services/­synapse-analytics
Technical documentationkylin.apache.org/­docsdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmldocs.featurebase.comdocs.microsoft.com/­azure/­synapse-analytics
DeveloperApache Software Foundation, originally contributed from eBay IncFairCom CorporationFatCloudMolecula and Pilosa Open Source ContributorsMicrosoft
Initial release20151979201220172016
Current release3.1.0, July 2020V13, July 20242022, May 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoRestricted, free version availablecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaANSI C, C++C#GoC++
Server operating systemsLinuxAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
WindowsLinux
macOS
hosted
Data schemeyesschema free, schema optional, schema required, partial schema,schema-freeyesyes
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyesyesyes
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 indexesyesyesyesnoyes
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)yes, ANSI SQL with proprietary extensionsno infoVia inetgration in SQL ServerSQL queriesyes
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
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC
JDBC
Kafka Connector
ODBC
ADO.NET
JDBC
ODBC
Supported programming languages.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C#Java
Python
C#
Java
PHP
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++yes infovia applicationsTransact SQL
Triggersyesyes infovia applicationsnono
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShardingShardingSharding, horizontal partitioning
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).selectable replication factoryesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnoyesno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraints
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datatunable from ACID to Eventually ConsistentnoyesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesYes, tunable from durable to delayed durability to in-memoryyesyes, using Linux fsyncyes
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 filesno infoCan implement custom security layer via applicationsyes

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More resources
Apache KylinFaircom DB infoformerly c-treeACEFatDBFeatureBaseMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse
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