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DBMS > Hypertable vs. Kinetica vs. Microsoft Azure Data Explorer vs. SWC-DB

System Properties Comparison Hypertable vs. Kinetica vs. Microsoft Azure Data Explorer vs. SWC-DB

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Editorial information provided by DB-Engines
NameHypertable  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  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 HadoopFully vectorized database across both GPUs and CPUsFully managed big data interactive analytics platformA high performance, scalable Wide Column DBMS
Primary database modelWide column storeRelational DBMSRelational DBMS infocolumn orientedWide column store
Secondary database modelsSpatial DBMS
Time Series DBMS
Document 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
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.01
Rank#376  Overall
#13  Wide column stores
Websitewww.kinetica.comazure.microsoft.com/­services/­data-explorergithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationdocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperHypertable Inc.KineticaMicrosoftAlex Kashirin
Initial release2009201220192020
Current release0.9.8.11, March 20167.1, August 2021cloud service with continuous releases0.5, April 2021
License infoCommercial or Open SourceOpen Source infoGNU version 3. Commercial license availablecommercialcommercialOpen Source infoGPL V3
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++C, C++C++
Server operating systemsLinux
OS X
Windows infoan inofficial Windows port is available
LinuxhostedLinux
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)schema-free
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.noyesno
Secondary indexesrestricted infoonly exact value or prefix value scansyesall fields are automatically indexed
SQL infoSupport of SQLnoSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetSQL-like query language
APIs and other access methodsC++ API
Thrift
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary protocol
Thrift
Supported programming languagesC++
Java
Perl
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++
Server-side scripts infoStored proceduresnouser defined functionsYes, possible languages: KQL, Python, Rno
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceSharding
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 methodsyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
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.yes infoGPU vRAM or System RAMnono
User concepts infoAccess controlnoAccess rights for users and roles on table levelAzure Active Directory Authentication

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More resources
HypertableKineticaMicrosoft Azure Data ExplorerSWC-DB infoSuper Wide Column Database
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