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DBMS > Apache Hive vs. Microsoft Azure Data Explorer vs. ReductStore

System Properties Comparison Apache Hive vs. Microsoft Azure Data Explorer vs. ReductStore

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Editorial information provided by DB-Engines
NameApache Hive  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonReductStore  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopFully managed big data interactive analytics platformDesigned to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.
Primary database modelRelational DBMSRelational DBMS infocolumn orientedTime Series 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
Score62.49
Rank#18  Overall
#12  Relational DBMS
Score2.98
Rank#83  Overall
#45  Relational DBMS
Score0.00
Rank#381  Overall
#40  Time Series DBMS
Websitehive.apache.orgazure.microsoft.com/­services/­data-explorergithub.com/­reductstore
www.reduct.store
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.microsoft.com/­en-us/­azure/­data-explorerwww.reduct.store/­docs
DeveloperApache Software Foundation infoinitially developed by FacebookMicrosoftReductStore LLC
Initial release201220192023
Current release3.1.3, April 2022cloud service with continuous releases1.9, March 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoBusiness Source License 1.1
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, Rust
Server operating systemsAll OS with a Java VMhostedDocker
Linux
macOS
Windows
Data schemeyesFixed schema with schema-less datatypes (dynamic)
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-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.yes
Secondary indexesyesall fields are automatically indexed
SQL infoSupport of SQLSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
ODBC
Thrift
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP API
Supported programming languagesC++
Java
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceYes, possible languages: KQL, Python, R
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud service
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.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlAccess rights for users, groups and rolesAzure Active Directory Authentication

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More resources
Apache HiveMicrosoft Azure Data ExplorerReductStore
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