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DBMS > Apache Jena - TDB vs. Hazelcast vs. HEAVY.AI vs. MarkLogic vs. Microsoft Azure Data Explorer

System Properties Comparison Apache Jena - TDB vs. Hazelcast vs. HEAVY.AI vs. MarkLogic vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameApache Jena - TDB  Xexclude from comparisonHazelcast  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonMarkLogic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionA RDF storage and query DBMS, shipped as an optional-use component of the Apache Jena frameworkA widely adopted in-memory data gridA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareOperational and transactional Enterprise NoSQL databaseFully managed big data interactive analytics platform
Primary database modelRDF storeKey-value storeRelational DBMSDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMS infocolumn oriented
Secondary database modelsDocument store infoJSON support with IMDG 3.12Spatial DBMSDocument 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
Score3.75
Rank#84  Overall
#3  RDF stores
Score5.97
Rank#57  Overall
#6  Key-value stores
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitejena.apache.org/­documentation/­tdb/­index.htmlhazelcast.comgithub.com/­heavyai/­heavydb
www.heavy.ai
www.marklogic.comazure.microsoft.com/­services/­data-explorer
Technical documentationjena.apache.org/­documentation/­tdb/­index.htmlhazelcast.org/­imdg/­docsdocs.heavy.aidocs.marklogic.comdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software Foundation infooriginally developed by HP LabsHazelcastHEAVY.AI, Inc.MarkLogic Corp.Microsoft
Initial release20002008201620012019
Current release4.9.0, July 20235.3.6, November 20235.10, January 202211.0, December 2022cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache License, Version 2.0Open Source infoApache Version 2; commercial licenses availableOpen Source infoApache Version 2; enterprise edition availablecommercial inforestricted free version is availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC++ and CUDAC++
Server operating systemsAll OS with a Java VMAll OS with a Java VMLinuxLinux
OS X
Windows
hosted
Data schemeyes infoRDF Schemasschema-freeyesschema-free infoSchema can be enforcedFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesyesyesyes 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 infothe object must implement a serialization strategynoyesyes
Secondary indexesyesyesnoyesall fields are automatically indexed
SQL infoSupport of SQLnoSQL-like query languageyesyes infoSQL92Kusto Query Language (KQL), SQL subset
APIs and other access methodsFuseki infoREST-style SPARQL HTTP Interface
Jena RDF API
RIO infoRDF Input/Output
JCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
Thrift
Vega
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesJava.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
All languages supporting JDBC/ODBC/Thrift
Python
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyesyes infoEvent Listeners, Executor Servicesnoyes infovia XQuery or JavaScriptYes, possible languages: KQL, Python, R
Triggersyes infovia event handleryes infoEventsnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoRound robinShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes infoReplicated MapMulti-source replicationyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoTDB Transactionsone or two-phase-commit; repeatable reads; read commitednoACID infocan act as a resource manager in an XA/JTA transactionno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes, with Range Indexesno
User concepts infoAccess controlAccess control via Jena SecurityRole-based access controlfine grained access rights according to SQL-standardRole-based access control at the document and subdocument levelsAzure Active Directory Authentication

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More resources
Apache Jena - TDBHazelcastHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022MarkLogicMicrosoft Azure Data Explorer
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