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DBMS > Apache Kylin vs. Atos Standard Common Repository vs. Badger vs. Faircom DB vs. Microsoft Azure Synapse Analytics

System Properties Comparison Apache Kylin vs. Atos Standard Common Repository vs. Badger vs. Faircom DB vs. Microsoft Azure Synapse Analytics

Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonBadger  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server
Primary database modelRelational DBMSDocument store
Key-value store
Key-value storeKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#172  Overall
#79  Relational DBMS
Score0.14
Rank#331  Overall
#49  Key-value stores
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Websitekylin.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorygithub.com/­dgraph-io/­badgerwww.faircom.com/­products/­faircom-dbazure.microsoft.com/­services/­synapse-analytics
Technical documentationkylin.apache.org/­docsgodoc.org/­github.com/­dgraph-io/­badgerdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmldocs.microsoft.com/­azure/­synapse-analytics
DeveloperApache Software Foundation, originally contributed from eBay IncAtos Convergence CreatorsDGraph LabsFairCom CorporationMicrosoft
Initial release20152016201719792016
Current release3.1.0, July 20201703V12, November 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0commercial infoRestricted, free version availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaGoANSI C, C++C++
Server operating systemsLinuxLinuxBSD
Linux
OS X
Solaris
Windows
AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
hosted
Data schemeyesSchema and schema-less with LDAP viewsschema-freeschema free, schema optional, schema required, partial schema,yes
Typing infopredefined data types such as float or dateyesoptionalnoyes, ANSI SQL Types, JSON, typed binary structuresyes
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.noyesnonono
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)nonoyes, ANSI SQL with proprietary extensionsyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
LDAPADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
ADO.NET
JDBC
ODBC
Supported programming languagesAll languages with LDAP bindingsGo.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C#
Java
PHP
Server-side scripts infoStored proceduresnonoyes info.Net, JavaScript, C/C++Transact SQL
Triggersyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionnoneFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningSharding, horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationnoneEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate Consistency
Foreign keys infoReferential integritynonoyesno 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 dataAtomic execution of specific operationsnotunable from ACID to Eventually ConsistentACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesYes, tunable from durable to delayed durability to in-memoryyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlLDAP bind authenticationnoFine grained access rights according to SQL-standard with additional protections for filesyes

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More resources
Apache KylinAtos Standard Common RepositoryBadgerFaircom DB infoformerly c-treeACEMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse
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