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DBMS > Apache Kylin vs. Faircom DB vs. Microsoft Azure Data Explorer vs. RavenDB vs. YDB

System Properties Comparison Apache Kylin vs. Faircom DB vs. Microsoft Azure Data Explorer vs. RavenDB vs. YDB

Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRavenDB  Xexclude from comparisonYDB  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 platformOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseA distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMS infocolumn orientedDocument storeDocument store
Relational 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
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.25
Rank#170  Overall
#77  Relational DBMS
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score2.84
Rank#101  Overall
#18  Document stores
Score0.33
Rank#287  Overall
#43  Document stores
#132  Relational DBMS
Websitekylin.apache.orgwww.faircom.com/­products/­faircom-dbazure.microsoft.com/­services/­data-explorerravendb.netgithub.com/­ydb-platform/­ydb
ydb.tech
Technical documentationkylin.apache.org/­docsdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmldocs.microsoft.com/­en-us/­azure/­data-explorerravendb.net/­docsydb.tech/­en/­docs
DeveloperApache Software Foundation, originally contributed from eBay IncFairCom CorporationMicrosoftHibernating RhinosYandex
Initial release20151979201920102019
Current release3.1.0, July 2020V12, November 2020cloud service with continuous releases5.4, July 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoRestricted, free version availablecommercialOpen Source infoAGPL version 3, commercial license availableOpen Source infoApache 2.0; commercial license available
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++C#
Server operating systemsLinuxAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
hostedLinux
macOS
Raspberry Pi
Windows
Linux
Data schemeyesschema free, schema optional, schema required, partial schema,Fixed schema with schema-less datatypes (dynamic)schema-freeFlexible Schema (defined schema, partial schema, schema free)
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-typesnoyes
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.nonoyesno
Secondary indexesyesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)yes, ANSI SQL with proprietary extensionsKusto Query Language (KQL), SQL subsetSQL-like query language (RQL)SQL-like query language (YQL)
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
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
RESTful HTTP API (DynamoDB compatible)
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
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++Yes, possible languages: KQL, Python, Ryesno
Triggersyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
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 serviceShardingSharding
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.Multi-source replicationActive-passive shard replication
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
Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Immediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datatunable from ACID to Eventually ConsistentnoACID, Cluster-wide transaction availableACID
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 AuthenticationAuthorization levels configured per client per databaseAccess rights defined for Yandex Cloud users

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More resources
Apache KylinFaircom DB infoformerly c-treeACEMicrosoft Azure Data ExplorerRavenDBYDB
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