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DBMS > Hypertable vs. LeanXcale vs. Linter vs. Microsoft Azure Data Explorer

System Properties Comparison Hypertable vs. LeanXcale vs. Linter vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameHypertable  Xexclude from comparisonLeanXcale  Xexclude from comparisonLinter  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionAn open source BigTable implementation based on distributed file systems such as HadoopA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesRDBMS for high security requirementsFully managed big data interactive analytics platform
Primary database modelWide column storeKey-value store
Relational DBMS
Relational DBMSRelational DBMS infocolumn oriented
Secondary database modelsSpatial 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
Score0.35
Rank#283  Overall
#41  Key-value stores
#128  Relational DBMS
Score0.10
Rank#350  Overall
#153  Relational DBMS
Score5.16
Rank#69  Overall
#37  Relational DBMS
Websitewww.leanxcale.comlinter.ruazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperHypertable Inc.LeanXcalerelex.ruMicrosoft
Initial release2009201519902019
Current release0.9.8.11, March 2016cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoGNU version 3. Commercial license availablecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C and C++
Server operating systemsLinux
OS X
Windows infoan inofficial Windows port is available
AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
hosted
Data schemeschema-freeyesyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or datenoyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-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.noyes
Secondary indexesrestricted infoonly exact value or prefix value scansyesall fields are automatically indexed
SQL infoSupport of SQLnoyes infothrough Apache DerbyyesKusto Query Language (KQL), SQL subset
APIs and other access methodsC++ API
Thrift
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC++
Java
Perl
PHP
Python
Ruby
C
Java
Scala
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnoyes infoproprietary syntax with the possibility to convert from PL/SQLYes, possible languages: KQL, Python, R
Triggersnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor on file system levelSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDno
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.yesno
User concepts infoAccess controlnofine grained access rights according to SQL-standardAzure Active Directory Authentication

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More resources
HypertableLeanXcaleLinterMicrosoft Azure Data Explorer
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