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DBMS > Apache Kylin vs. Atos Standard Common Repository vs. Faircom DB vs. Microsoft Azure Data Explorer vs. OrientDB

System Properties Comparison Apache Kylin vs. Atos Standard Common Repository vs. Faircom DB vs. Microsoft Azure Data Explorer vs. OrientDB

Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOrientDB  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 networksNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Fully managed big data interactive analytics platformMulti-model DBMS (Document, Graph, Key/Value)
Primary database modelRelational DBMSDocument store
Key-value store
Key-value store
Relational DBMS
Relational DBMS infocolumn orientedDocument store
Graph DBMS
Key-value store
Secondary database modelsDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#172  Overall
#79  Relational DBMS
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score3.19
Rank#93  Overall
#16  Document stores
#7  Graph DBMS
#14  Key-value stores
Websitekylin.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.faircom.com/­products/­faircom-dbazure.microsoft.com/­services/­data-explorerorientdb.org
Technical documentationkylin.apache.org/­docsdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmldocs.microsoft.com/­en-us/­azure/­data-explorerwww.orientdb.com/­docs/­last/­index.html
DeveloperApache Software Foundation, originally contributed from eBay IncAtos Convergence CreatorsFairCom CorporationMicrosoftOrientDB LTD; CallidusCloud; SAP
Initial release20152016197920192010
Current release3.1.0, July 20201703V12, November 2020cloud service with continuous releases3.2.29, March 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial infoRestricted, free version availablecommercialOpen Source infoApache version 2
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaANSI C, C++Java
Server operating systemsLinuxLinuxAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
hostedAll OS with a Java JDK (>= JDK 6)
Data schemeyesSchema and schema-less with LDAP viewsschema free, schema optional, schema required, partial schema,Fixed schema with schema-less datatypes (dynamic)schema-free infoSchema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")
Typing infopredefined data types such as float or dateyesoptionalyes, ANSI SQL Types, JSON, typed binary structuresyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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.noyesnoyesno
Secondary indexesyesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)noyes, ANSI SQL with proprietary extensionsKusto Query Language (KQL), SQL subsetSQL-like query language, no joins
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
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API
Supported programming languagesAll languages with LDAP bindings.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++Yes, possible languages: KQL, Python, RJava, Javascript
Triggersyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyHooks
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno infocould be achieved with distributed queries
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnoyes inforelationship in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationstunable from ACID to Eventually ConsistentnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesYes, 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 controlLDAP bind authenticationFine grained access rights according to SQL-standard with additional protections for filesAzure Active Directory AuthenticationAccess rights for users and roles; record level security configurable

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More resources
Apache KylinAtos Standard Common RepositoryFaircom DB infoformerly c-treeACEMicrosoft Azure Data ExplorerOrientDB
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