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DBMS > Hive vs. Kinetica vs. Microsoft Azure Data Explorer vs. RDF4J vs. Speedb

System Properties Comparison Hive vs. Kinetica vs. Microsoft Azure Data Explorer vs. RDF4J vs. Speedb

Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSpeedb  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopFully vectorized database across both GPUs and CPUsFully managed big data interactive analytics platformRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.An embeddable, high performance key-value store optimized for write-intensive workloads, which can be used as a drop-in replacement for RocksDB
Primary database modelRelational DBMSRelational DBMSRelational DBMS infocolumn orientedRDF storeKey-value store
Secondary database modelsSpatial DBMS
Time Series 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
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Score0.21
Rank#315  Overall
#45  Key-value stores
Websitehive.apache.orgwww.kinetica.comazure.microsoft.com/­services/­data-explorerrdf4j.orgwww.speedb.io
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­data-explorerrdf4j.org/­documentation
DeveloperApache Software Foundation infoinitially developed by FacebookKineticaMicrosoftSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Speedb
Initial release20122012201920042020
Current release3.1.3, April 20227.1, August 2021cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoApache Version 2.0; commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++JavaC++
Server operating systemsAll OS with a Java VMLinuxhostedLinux
OS X
Unix
Windows
Linux
Windows
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)yes infoRDF Schemasschema-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-typesyesno
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 indexedyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetnono
APIs and other access methodsJDBC
ODBC
Thrift
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesC++
Java
PHP
Python
C++
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
PHP
Python
C
C++
Go
Java
Perl
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functionsYes, possible languages: KQL, Python, Ryesno
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud servicenonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID infoIsolation support depends on the API usedyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMnoyes
User concepts infoAccess controlAccess rights for users, groups and rolesAccess rights for users and roles on table levelAzure Active Directory Authenticationnono
More information provided by the system vendor
HiveKineticaMicrosoft Azure Data ExplorerRDF4J infoformerly known as SesameSpeedb
Specific characteristicsSpeedb is an embedded key-value storage engine for versatile use cases. It was designed...
» more
Competitive advantagesSpeedb Open-source rebases on RocksDB's latest versions, with enhanced capabilities...
» more
Licensing and pricing modelsOpen source - Speedb OSS is released under an Apache license and can be found on...
» more

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HiveKineticaMicrosoft Azure Data ExplorerRDF4J infoformerly known as SesameSpeedb
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