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DBMS > EsgynDB vs. Ingres vs. Microsoft Azure Data Explorer vs. Prometheus vs. Sphinx

System Properties Comparison EsgynDB vs. Ingres vs. Microsoft Azure Data Explorer vs. Prometheus vs. Sphinx

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonIngres  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPrometheus  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionWell established RDBMSFully managed big data interactive analytics platformOpen-source Time Series DBMS and monitoring systemOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSRelational DBMSRelational DBMS infocolumn orientedTime Series DBMSSearch engine
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
Score3.80
Rank#82  Overall
#44  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitewww.esgyn.cnwww.actian.com/­databases/­ingresazure.microsoft.com/­services/­data-explorerprometheus.iosphinxsearch.com
Technical documentationdocs.actian.com/­ingresdocs.microsoft.com/­en-us/­azure/­data-explorerprometheus.io/­docssphinxsearch.com/­docs
DeveloperEsgynActian CorporationMicrosoftSphinx Technologies Inc.
Initial release20151974 infooriginally developed at University Berkely in early 1970s201920152001
Current release11.2, May 2022cloud service with continuous releases3.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaCGoC++
Server operating systemsLinuxAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
hostedLinux
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)yesyes
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-typesNumeric data onlyno
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.nono infobut tools for importing/exporting data from/to XML-files availableyesno infoImport of XML data possible
Secondary indexesyesyesall fields are automatically indexednoyes infofull-text index on all search fields
SQL infoSupport of SQLyesyesKusto Query Language (KQL), SQL subsetnoSQL-like query language (SphinxQL)
APIs and other access methodsADO.NET
JDBC
ODBC
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP/JSON APIProprietary protocol
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresJava Stored ProceduresyesYes, possible languages: KQL, Python, Rnono
Triggersnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding infoImplicit feature of the cloud serviceShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersIngres Replicatoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes infoby Federationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
none
Foreign keys infoReferential integrityyesyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyes infoMVCCyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononono
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardAzure Active Directory Authenticationnono

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More resources
EsgynDBIngresMicrosoft Azure Data ExplorerPrometheusSphinx
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