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DBMS > Amazon DocumentDB vs. Apache Jena - TDB vs. Microsoft Access vs. Sphinx vs. Splice Machine

System Properties Comparison Amazon DocumentDB vs. Apache Jena - TDB vs. Microsoft Access vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache Jena - TDB  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceA RDF storage and query DBMS, shipped as an optional-use component of the Apache Jena frameworkMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)Open source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument storeRDF storeRelational DBMSSearch engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score3.75
Rank#84  Overall
#3  RDF stores
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteaws.amazon.com/­documentdbjena.apache.org/­documentation/­tdb/­index.htmlwww.microsoft.com/­en-us/­microsoft-365/­accesssphinxsearch.comsplicemachine.com
Technical documentationaws.amazon.com/­documentdb/­resourcesjena.apache.org/­documentation/­tdb/­index.htmldeveloper.microsoft.com/­en-us/­accesssphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperApache Software Foundation infooriginally developed by HP LabsMicrosoftSphinx Technologies Inc.Splice Machine
Initial release20192000199220012014
Current release4.9.0, July 20231902 (16.0.11328.20222), March 20193.5.1, February 20233.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache License, Version 2.0commercial infoBundled with Microsoft OfficeOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C++Java
Server operating systemshostedAll OS with a Java VMWindows infoNot a real database server, but making use of DLLsFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyes infoRDF Schemasyesyesyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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.no
Secondary indexesyesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnonoyes infobut not compliant to any SQL standardSQL-like query language (SphinxQL)yes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)Fuseki infoREST-style SPARQL HTTP Interface
Jena RDF API
RIO infoRDF Input/Output
ADO.NET
DAO
ODBC
OLE DB
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
JavaC
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyesyes infosince Access 2010 using the ACE-enginenoyes infoJava
Triggersnoyes infovia event handleryes infosince Access 2010 using the ACE-enginenoyes
Partitioning methods infoMethods for storing different data on different nodesnonenonenoneSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasnonenonenoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACID infoTDB TransactionsACID infobut no files for transaction loggingnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infobut no files for transaction loggingyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
User concepts infoAccess controlAccess rights for users and rolesAccess control via Jena Securityno infoa simple user-level security was built in till version Access 2003noAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon DocumentDBApache Jena - TDBMicrosoft AccessSphinxSplice Machine
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