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DBMS > Hive vs. Microsoft Azure Table Storage vs. Spark SQL vs. TerminusDB vs. Tkrzw

System Properties Comparison Hive vs. Microsoft Azure Table Storage vs. Spark SQL vs. TerminusDB vs. Tkrzw

Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSpark SQL  Xexclude from comparisonTerminusDB infoformer name was DataChemist  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopA Wide Column Store for rapid development using massive semi-structured datasetsSpark SQL is a component on top of 'Spark Core' for structured data processingScalable Graph Database platform making enterprise data available by exploiting inferred entities and relationshipsA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelRelational DBMSWide column storeRelational DBMSGraph DBMSKey-value store
Secondary database modelsDocument store
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.23
Rank#316  Overall
#27  Graph DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websitehive.apache.orgazure.microsoft.com/­en-us/­services/­storage/­tablesspark.apache.org/­sqlterminusdb.comdbmx.net/­tkrzw
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homespark.apache.org/­docs/­latest/­sql-programming-guide.htmlterminusdb.github.io/­terminusdb/­#
DeveloperApache Software Foundation infoinitially developed by FacebookMicrosoftApache Software FoundationDataChemist Ltd.Mikio Hirabayashi
Initial release20122012201420182020
Current release3.1.3, April 20223.5.0 ( 2.13), September 202311.0.0, January 20230.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache 2.0Open Source infoGPL V3Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaProlog, RustC++
Server operating systemsAll OS with a Java VMhostedLinux
OS X
Windows
LinuxLinux
macOS
Data schemeyesschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyesno
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.nononono
Secondary indexesyesnono
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like DML and DDL statementsSQL-like query language (WOQL)no
APIs and other access methodsJDBC
ODBC
Thrift
RESTful HTTP APIJDBC
ODBC
OWL
RESTful HTTP API
WOQL (Web Object Query Language)
Supported programming languagesC++
Java
PHP
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
JavaScript
Python
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonoyesno
Triggersnononoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceyes, utilizing Spark CoreGraph Partitioningnone
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.noneJournaling Streamsnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory journalingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infousing specific database classes
User concepts infoAccess controlAccess rights for users, groups and rolesAccess rights based on private key authentication or shared access signaturesnoRole-based access controlno

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More resources
HiveMicrosoft Azure Table StorageSpark SQLTerminusDB infoformer name was DataChemistTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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