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DBMS > Apache Impala vs. Microsoft Access vs. Microsoft Azure AI Search vs. RDFox vs. Titan

System Properties Comparison Apache Impala vs. Microsoft Access vs. Microsoft Azure AI Search vs. RDFox vs. Titan

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonRDFox  Xexclude from comparisonTitan  Xexclude from comparison
Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.
DescriptionAnalytic DBMS for HadoopMicrosoft 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.)Search-as-a-service for web and mobile app developmentHigh performance knowledge graph and semantic reasoning engineTitan is a Graph DBMS optimized for distributed clusters.
Primary database modelRelational DBMSRelational DBMSSearch engineGraph DBMS
RDF store
Graph DBMS
Secondary database modelsDocument storeVector DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score101.16
Rank#11  Overall
#8  Relational DBMS
Score5.52
Rank#59  Overall
#6  Search engines
Score0.29
Rank#300  Overall
#24  Graph DBMS
#13  RDF stores
Websiteimpala.apache.orgwww.microsoft.com/­en-us/­microsoft-365/­accessazure.microsoft.com/­en-us/­services/­searchwww.oxfordsemantic.techgithub.com/­thinkaurelius/­titan
Technical documentationimpala.apache.org/­impala-docs.htmldeveloper.microsoft.com/­en-us/­accesslearn.microsoft.com/­en-us/­azure/­searchdocs.oxfordsemantic.techgithub.com/­thinkaurelius/­titan/­wiki
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaMicrosoftMicrosoftOxford Semantic TechnologiesAurelius, owned by DataStax
Initial release20131992201520172012
Current release4.1.0, June 20221902 (16.0.11328.20222), March 2019V16.0, Septermber 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infoBundled with Microsoft OfficecommercialcommercialOpen Source infoApache license, version 2.0
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 languageC++C++C++Java
Server operating systemsLinuxWindows infoNot a real database server, but making use of DLLshostedLinux
macOS
Windows
Linux
OS X
Unix
Windows
Data schemeyesyesyesyes infoRDF schemasyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infobut not compliant to any SQL standardnonono
APIs and other access methodsJDBC
ODBC
ADO.NET
DAO
ODBC
OLE DB
RESTful HTTP APIRESTful HTTP API
SPARQL 1.1
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
C#
Java
JavaScript
Python
C
Java
Clojure
Java
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infosince Access 2010 using the ACE-enginenoyes
Triggersnoyes infosince Access 2010 using the ACE-enginenoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoImplicit feature of the cloud serviceyes infovia pluggable storage backends
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneyes infoImplicit feature of the cloud servicereplication via a shared file systemyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoyes infovia Faunus, a graph analytics engine
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency in stand-alone mode, Eventual Consistency in replicated setupsEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnoyes infoRelationships in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infobut no files for transaction loggingnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infobut no files for transaction loggingyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosno infoa simple user-level security was built in till version Access 2003yes infousing Azure authenticationRoles, resources, and access typesUser authentification and security via Rexster Graph Server

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More resources
Apache ImpalaMicrosoft AccessMicrosoft Azure AI SearchRDFoxTitan
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