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DBMS > EsgynDB vs. Graph Engine vs. Microsoft Azure Data Explorer vs. Warp 10

System Properties Comparison EsgynDB vs. Graph Engine vs. Microsoft Azure Data Explorer vs. Warp 10

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineFully managed big data interactive analytics platformTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelRelational DBMSGraph DBMS
Key-value store
Relational DBMS infocolumn orientedTime Series DBMS
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
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.07
Rank#349  Overall
#32  Time Series DBMS
Websitewww.esgyn.cnwww.graphengine.ioazure.microsoft.com/­services/­data-explorerwww.warp10.io
Technical documentationwww.graphengine.io/­docs/­manualdocs.microsoft.com/­en-us/­azure/­data-explorerwww.warp10.io/­content/­02_Getting_started
DeveloperEsgynMicrosoftMicrosoftSenX
Initial release2015201020192015
Current releasecloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoMIT LicensecommercialOpen Source infoApache License 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.NET and CJava
Server operating systemsLinux.NEThostedLinux
OS X
Windows
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)schema-free
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.nonoyesno
Secondary indexesyesall fields are automatically indexedno
SQL infoSupport of SQLyesnoKusto Query Language (KQL), SQL subsetno
APIs and other access methodsADO.NET
JDBC
ODBC
RESTful HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP API
Jupyter
WebSocket
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
F#
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresJava Stored ProceduresyesYes, possible languages: KQL, Python, Ryes infoWarpScript
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningSharding infoImplicit feature of the cloud serviceSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency infobased on HBase
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAzure Active Directory AuthenticationMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
EsgynDBGraph Engine infoformer name: TrinityMicrosoft Azure Data ExplorerWarp 10
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