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DBMS > EXASOL vs. Hive vs. Microsoft Azure Data Explorer vs. Qdrant

System Properties Comparison EXASOL vs. Hive vs. Microsoft Azure Data Explorer vs. Qdrant

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Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonHive  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonQdrant  Xexclude from comparison
DescriptionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.data warehouse software for querying and managing large distributed datasets, built on HadoopFully managed big data interactive analytics platformA high-performance vector database with neural network or semantic-based matching
Primary database modelRelational DBMSRelational DBMSRelational DBMS infocolumn orientedVector 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
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score1.16
Rank#175  Overall
#6  Vector DBMS
Websitewww.exasol.comhive.apache.orgazure.microsoft.com/­services/­data-explorergithub.com/­qdrant/­qdrant
qdrant.tech
Technical documentationwww.exasol.com/­resourcescwiki.apache.org/­confluence/­display/­Hive/­Homedocs.microsoft.com/­en-us/­azure/­data-explorerqdrant.tech/­documentation
DeveloperExasolApache Software Foundation infoinitially developed by FacebookMicrosoftQdrant
Initial release2000201220192021
Current release3.1.3, April 2022cloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialOpen Source infoApache Version 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 languageJavaRust
Server operating systemsAll OS with a Java VMhostedDocker
Linux
macOS
Windows
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)schema-free
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-typesNumbers, Strings, Geo, Boolean
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 indexesyesyesall fields are automatically indexedyes infoKeywords, numberic ranges, geo, full-text
SQL infoSupport of SQLyesSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetno
APIs and other access methods.Net
JDBC
ODBC
WebSocket
JDBC
ODBC
Thrift
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
gRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
Supported programming languagesJava
Lua
Python
R
C++
Java
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresuser defined functionsyes infouser defined functions and integration of map-reduceYes, possible languages: KQL, Python, R
Triggersyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
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 nodesselectable replication factoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Collection-level replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationyes infoquery execution via MapReduceSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency, tunable consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
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.yesnoyes
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardAccess rights for users, groups and rolesAzure Active Directory AuthenticationKey-based authentication

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More resources
EXASOLHiveMicrosoft Azure Data ExplorerQdrant
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