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DBMS > EXASOL vs. GridDB vs. Microsoft Azure Data Explorer vs. Prometheus

System Properties Comparison EXASOL vs. GridDB vs. Microsoft Azure Data Explorer vs. Prometheus

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Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonGridDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPrometheus  Xexclude from comparison
DescriptionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Scalable in-memory time series database optimized for IoT and Big DataFully managed big data interactive analytics platformOpen-source Time Series DBMS and monitoring system
Primary database modelRelational DBMSTime Series DBMSRelational DBMS infocolumn orientedTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
Document 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
Score1.66
Rank#138  Overall
#64  Relational DBMS
Score1.91
Rank#123  Overall
#10  Time Series DBMS
Score3.28
Rank#83  Overall
#45  Relational DBMS
Score7.56
Rank#49  Overall
#3  Time Series DBMS
Websitewww.exasol.comgriddb.netazure.microsoft.com/­services/­data-explorerprometheus.io
Technical documentationwww.exasol.com/­resourcesdocs.griddb.netdocs.microsoft.com/­en-us/­azure/­data-explorerprometheus.io/­docs
DeveloperExasolToshiba CorporationMicrosoft
Initial release2000201320192015
Current release5.1, August 2022cloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialOpen Source infoApache 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++Go
Server operating systemsLinuxhostedLinux
Windows
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesNumeric data only
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 infoImport of XML data possible
Secondary indexesyesyesall fields are automatically indexedno
SQL infoSupport of SQLyesSQL92, SQL-like TQL (Toshiba Query Language)Kusto Query Language (KQL), SQL subsetno
APIs and other access methods.Net
JDBC
ODBC
WebSocket
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP/JSON API
Supported programming languagesJava
Lua
Python
R
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsnoYes, possible languages: KQL, Python, Rno
Triggersyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes infoby Federation
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersEventual Consistency
Immediate Consistency
none
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelnono
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.yesyesnono
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardAccess rights for users can be defined per databaseAzure Active Directory Authenticationno

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More resources
EXASOLGridDBMicrosoft Azure Data ExplorerPrometheus
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