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DBMS > EsgynDB vs. Microsoft Azure Data Explorer vs. Splice Machine vs. Trafodion

System Properties Comparison EsgynDB vs. Microsoft Azure Data Explorer vs. Splice Machine vs. Trafodion

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSplice Machine  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionFully managed big data interactive analytics platformOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkTransactional SQL-on-Hadoop DBMS
Primary database modelRelational DBMSRelational DBMS infocolumn orientedRelational DBMSRelational 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
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.esgyn.cnazure.microsoft.com/­services/­data-explorersplicemachine.comtrafodion.apache.org
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorersplicemachine.com/­how-it-workstrafodion.apache.org/­documentation.html
DeveloperEsgynMicrosoftSplice MachineApache Software Foundation, originally developed by HP
Initial release2015201920142014
Current releasecloud service with continuous releases3.1, March 20212.3.0, February 2019
License infoCommercial or Open SourcecommercialcommercialOpen Source infoAGPL 3.0, commercial license availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaJavaC++, Java
Server operating systemsLinuxhostedLinux
OS X
Solaris
Windows
Linux
Data schemeyesFixed schema with schema-less datatypes (dynamic)yesyes
Typing infopredefined data types such as float or dateyesyes 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.noyesno
Secondary indexesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLyesKusto Query Language (KQL), SQL subsetyesyes
APIs and other access methodsADO.NET
JDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
ADO.NET
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresJava Stored ProceduresYes, possible languages: KQL, Python, Ryes infoJavaJava Stored Procedures
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceShared Nothhing Auto-Sharding, Columnar PartitioningSharding
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.Multi-source replication
Source-replica replication
yes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkYes, via Full Spark Integrationyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
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.nonoyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAzure Active Directory AuthenticationAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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More resources
EsgynDBMicrosoft Azure Data ExplorerSplice MachineTrafodion
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