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DBMS > Apache Kylin vs. Faircom DB vs. Microsoft Azure Data Explorer vs. Riak KV vs. TimescaleDB

System Properties Comparison Apache Kylin vs. Faircom DB vs. Microsoft Azure Data Explorer vs. Riak KV vs. TimescaleDB

Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRiak KV  Xexclude from comparisonTimescaleDB  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.Fully managed big data interactive analytics platformDistributed, fault tolerant key-value storeA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMS infocolumn orientedKey-value store infowith links between data sets and object tags for the creation of secondary indexesTime Series DBMS
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
Relational DBMS
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
Score4.10
Rank#82  Overall
#9  Key-value stores
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitekylin.apache.orgwww.faircom.com/­products/­faircom-dbazure.microsoft.com/­services/­data-explorerwww.timescale.com
Technical documentationkylin.apache.org/­docsdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmldocs.microsoft.com/­en-us/­azure/­data-explorerwww.tiot.jp/­riak-docs/­riak/­kv/­latestdocs.timescale.com
DeveloperApache Software Foundation, originally contributed from eBay IncFairCom CorporationMicrosoftOpenSource, formerly Basho TechnologiesTimescale
Initial release20151979201920092017
Current release3.1.0, July 2020V12, November 2020cloud service with continuous releases3.2.0, December 20222.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoRestricted, free version availablecommercialOpen Source infoApache version 2, commercial enterprise editionOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaANSI C, C++ErlangC
Server operating systemsLinuxAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
hostedLinux
OS X
Linux
OS X
Windows
Data schemeyesschema free, schema optional, schema required, partial schema,Fixed schema with schema-less datatypes (dynamic)schema-freeyes
Typing infopredefined data types such as float or dateyesyes, 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-typesnonumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nonoyesnoyes
Secondary indexesyesyesall fields are automatically indexedrestrictedyes
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)yes, ANSI SQL with proprietary extensionsKusto Query Language (KQL), SQL subsetnoyes infofull PostgreSQL SQL syntax
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
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP API
Native Erlang Interface
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++Yes, possible languages: KQL, Python, RErlanguser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infopre-commit hooks and post-commit hooksyes
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningSharding infoImplicit feature of the cloud serviceSharding infono "single point of failure"yes, across time and space (hash partitioning) attributes
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 infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factorSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesno
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
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnono infolinks between data sets can be storedyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datatunable from ACID to Eventually ConsistentnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesYes, tunable from durable to delayed durability to in-memoryyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesAzure Active Directory Authenticationyes, using Riak Securityfine grained access rights according to SQL-standard

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More resources
Apache KylinFaircom DB infoformerly c-treeACEMicrosoft Azure Data ExplorerRiak KVTimescaleDB
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