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DBMS > Hive vs. HugeGraph vs. Microsoft Azure Data Explorer vs. Trafodion

System Properties Comparison Hive vs. HugeGraph vs. Microsoft Azure Data Explorer vs. Trafodion

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Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonHugeGraph  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopA fast-speed and highly-scalable Graph DBMSFully managed big data interactive analytics platformTransactional SQL-on-Hadoop DBMS
Primary database modelRelational DBMSGraph DBMSRelational DBMS infocolumn orientedRelational 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
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websitehive.apache.orggithub.com/­hugegraph
hugegraph.apache.org
azure.microsoft.com/­services/­data-explorertrafodion.apache.org
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homehugegraph.apache.org/­docsdocs.microsoft.com/­en-us/­azure/­data-explorertrafodion.apache.org/­documentation.html
DeveloperApache Software Foundation infoinitially developed by FacebookBaiduMicrosoftApache Software Foundation, originally developed by HP
Initial release2012201820192014
Current release3.1.3, April 20220.9cloud service with continuous releases2.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++, Java
Server operating systemsAll OS with a Java VMLinux
macOS
Unix
hostedLinux
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)yes
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-typesyes
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 indexesyesyes infoalso supports composite index and range indexall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoKusto Query Language (KQL), SQL subsetyes
APIs and other access methodsJDBC
ODBC
Thrift
Java API
RESTful HTTP API
TinkerPop Gremlin
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
ODBC
Supported programming languagesC++
Java
PHP
Python
Groovy
Java
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceasynchronous Gremlin script jobsYes, possible languages: KQL, Python, RJava Stored Procedures
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infodepending on used storage backend, e.g. Cassandra and HBaseyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducevia hugegraph-sparkSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infoedges in graphnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
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.yesnono
User concepts infoAccess controlAccess rights for users, groups and rolesUsers, roles and permissionsAzure Active Directory Authenticationfine grained access rights according to SQL-standard

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HiveHugeGraphMicrosoft Azure Data ExplorerTrafodion
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