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DBMS > DataFS vs. Ignite vs. Microsoft Azure Data Explorer vs. Spark SQL

System Properties Comparison DataFS vs. Ignite vs. Microsoft Azure Data Explorer vs. Spark SQL

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Editorial information provided by DB-Engines
NameDataFS  Xexclude from comparisonIgnite  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAll data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Fully managed big data interactive analytics platformSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelObject oriented DBMSKey-value store
Relational DBMS
Relational DBMS infocolumn orientedRelational DBMS
Secondary database modelsGraph DBMSDocument 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
Score0.06
Rank#354  Overall
#15  Object oriented DBMS
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitenewdatabase.comignite.apache.orgazure.microsoft.com/­services/­data-explorerspark.apache.org/­sql
Technical documentationdev.mobiland.com/­Overview.xspapacheignite.readme.io/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMobiland AGApache Software FoundationMicrosoftApache Software Foundation
Initial release2018201520192014
Current release1.1.263, October 2022Apache Ignite 2.6cloud service with continuous releases3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, Java, .NetScala
Server operating systemsWindowsLinux
OS X
Solaris
Windows
hostedLinux
OS X
Windows
Data schemeClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)yesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesyes 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.noyesyesno
Secondary indexesnoyesall fields are automatically indexedno
SQL infoSupport of SQLnoANSI-99 for query and DML statements, subset of DDLKusto Query Language (KQL), SQL subsetSQL-like DML and DDL statements
APIs and other access methods.NET Client API
Proprietary client DLL
WinRT client
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
Supported programming languages.Net
C
C#
C++
VB.Net
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)Yes, possible languages: KQL, Python, Rno
Triggersno, except callback-events from server when changes happenedyes (cache interceptors and events)yes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesProprietary Sharding systemShardingSharding infoImplicit feature of the cloud serviceyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)Spark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlWindows-ProfileSecurity Hooks for custom implementationsAzure Active Directory Authenticationno

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More resources
DataFSIgniteMicrosoft Azure Data ExplorerSpark SQL
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