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DBMS > EsgynDB vs. Hypertable vs. Kyligence Enterprise vs. Microsoft Azure Data Explorer

System Properties Comparison EsgynDB vs. Hypertable vs. Kyligence Enterprise vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonHypertable  Xexclude from comparisonKyligence Enterprise  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.
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionAn open source BigTable implementation based on distributed file systems such as HadoopA distributed analytics engine for big data, built on top of Apache KylinFully managed big data interactive analytics platform
Primary database modelRelational DBMSWide column storeRelational DBMSRelational DBMS infocolumn oriented
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
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score0.46
Rank#266  Overall
#124  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websitewww.esgyn.cnkyligence.io/­kyligence-enterpriseazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperEsgynHypertable Inc.Kyligence, Inc.Microsoft
Initial release2015200920162019
Current release0.9.8.11, March 2016cloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoGNU version 3. Commercial license availablecommercialcommercial
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++, JavaC++Java
Server operating systemsLinuxLinux
OS X
Windows infoan inofficial Windows port is available
Linuxhosted
Data schemeyesschema-freeyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesnoyesyes 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.nonoyes
Secondary indexesyesrestricted infoonly exact value or prefix value scansyesall fields are automatically indexed
SQL infoSupport of SQLyesnoANSI SQL for queries (using Apache Calcite)Kusto Query Language (KQL), SQL subset
APIs and other access methodsADO.NET
JDBC
ODBC
C++ API
Thrift
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC++
Java
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresJava Stored ProceduresnoYes, possible languages: KQL, Python, R
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersselectable replication factor on file system levelyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesyesSpark 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 integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
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.nonono
User concepts infoAccess controlfine grained access rights according to SQL-standardnoAzure Active Directory Authentication

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More resources
EsgynDBHypertableKyligence EnterpriseMicrosoft Azure Data Explorer
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