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DBMS > EXASOL vs. Microsoft Azure Data Explorer vs. Percona Server for MongoDB vs. STSdb vs. Vertica

System Properties Comparison EXASOL vs. Microsoft Azure Data Explorer vs. Percona Server for MongoDB vs. STSdb vs. Vertica

Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPercona Server for MongoDB  Xexclude from comparisonSTSdb  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Fully managed big data interactive analytics platformA drop-in replacement for MongoDB Community Edition with enterprise-grade features.Key-Value Store with special method for indexing infooptimized for high performance using a special indexing methodCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelRelational DBMSRelational DBMS infocolumn orientedDocument storeKey-value storeRelational DBMS infoColumn oriented
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
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.76
Rank#139  Overall
#62  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.60
Rank#246  Overall
#39  Document stores
Score0.10
Rank#357  Overall
#51  Key-value stores
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitewww.exasol.comazure.microsoft.com/­services/­data-explorerwww.percona.com/­mongodb/­software/­percona-server-for-mongodbgithub.com/­STSSoft/­STSdb4www.vertica.com
Technical documentationwww.exasol.com/­resourcesdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.percona.com/­percona-distribution-for-mongodbvertica.com/­documentation
DeveloperExasolMicrosoftPerconaSTS Soft SCOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20002019201520112005
Current releasecloud service with continuous releases3.4.10-2.10, November 20174.0.8, September 201512.0.3, January 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL Version 2Open Source infoGPLv2, commercial license availablecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenoyesnonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C#C++
Server operating systemshostedLinuxWindowsLinux
Data schemeyesFixed schema with schema-less datatypes (dynamic)schema-freeyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
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 infoprimitive types and user defined types (classes)yes
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.noyesnono
Secondary indexesyesall fields are automatically indexedyesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesKusto Query Language (KQL), SQL subsetnonoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methods.Net
JDBC
ODBC
WebSocket
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
proprietary protocol using JSON.NET Client APIADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesJava
Lua
Python
R
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk
C#
Java
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functionsYes, possible languages: KQL, Python, RJavaScriptnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynonoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceShardingnonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationnoneMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infovia In-Memory Engineno
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardAzure Active Directory AuthenticationAccess rights for users and rolesnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
EXASOLMicrosoft Azure Data ExplorerPercona Server for MongoDBSTSdbVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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EXASOLMicrosoft Azure Data ExplorerPercona Server for MongoDBSTSdbVertica infoOpenText™ Vertica™
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