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DBMS > EsgynDB vs. Greenplum vs. InterSystems Caché vs. Microsoft Azure Data Explorer

System Properties Comparison EsgynDB vs. Greenplum vs. InterSystems Caché vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGreenplum  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.A multi-model DBMS and application serverFully managed big data interactive analytics platform
Primary database modelRelational DBMSRelational DBMSKey-value store
Object oriented DBMS
Relational DBMS
Relational DBMS infocolumn oriented
Secondary database modelsDocument store
Spatial DBMS
Document storeDocument 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
Score8.37
Rank#48  Overall
#30  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitewww.esgyn.cngreenplum.orgwww.intersystems.com/­products/­cacheazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.greenplum.orgdocs.intersystems.comdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperEsgynPivotal Software Inc.InterSystemsMicrosoft
Initial release2015200519972019
Current release7.0.0, September 20232018.1.4, May 2020cloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, Java
Server operating systemsLinuxLinuxAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
hosted
Data schemeyesyesdepending on used data modelFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesyesyes 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 infosince Version 4.2yesyes
Secondary indexesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLyesyesyesKusto Query Language (KQL), SQL subset
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
.NET Client API
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
Python
R
C#
C++
Java
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresJava Stored ProceduresyesyesYes, possible languages: KQL, Python, R
Triggersnoyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersSource-replica replicationSource-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 methodsyesyesnoSpark 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 integrityyesyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
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.nonoyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardAccess rights for users, groups and rolesAzure Active Directory Authentication

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More resources
EsgynDBGreenplumInterSystems CachéMicrosoft Azure Data Explorer
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