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DBMS > Microsoft Azure Data Explorer vs. Splice Machine vs. Typesense

System Properties Comparison Microsoft Azure Data Explorer vs. Splice Machine vs. Typesense

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Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonSplice Machine  Xexclude from comparisonTypesense  Xexclude from comparison
DescriptionFully managed big data interactive analytics platformOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity
Primary database modelRelational DBMS infocolumn orientedRelational DBMSSearch engine
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
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.79
Rank#210  Overall
#14  Search engines
Websiteazure.microsoft.com/­services/­data-explorersplicemachine.comtypesense.org
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorersplicemachine.com/­how-it-workstypesense.org/­docs
DeveloperMicrosoftSplice Machine
Initial release201920142015
Current releasecloud service with continuous releases3.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoAGPL 3.0, commercial license availableOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++
Server operating systemshostedLinux
OS X
Solaris
Windows
Linux
Data schemeFixed schema with schema-less datatypes (dynamic)yesschema-free infopre-defined schema optional
Typing infopredefined data types such as float or dateyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes
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.yes
Secondary indexesall fields are automatically indexedyesyes
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetyesno
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
RESTful HTTP API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
.Net infocommunity maintained
Clojure infocommunity maintained
Dart infocommunity maintained
Go infocommunity maintained
Java infocommunity maintained
JavaScript
Perl infocommunity maintained
PHP
Python
Ruby
Rust infocommunity maintained
Swift infocommunity maintained
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, Ryes infoJavano
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
Multi-source replication using RAFT
MapReduce infoOffers an API for user-defined Map/Reduce methodsSpark connector (open source): github.com/­Azure/­azure-kusto-sparkYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlAzure Active Directory AuthenticationAccess rights for users, groups and roles according to SQL-standard

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More resources
Microsoft Azure Data ExplorerSplice MachineTypesense
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