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DBMS > Apache Impala vs. Apache IoTDB vs. Atos Standard Common Repository vs. Interbase vs. Microsoft Access

System Properties Comparison Apache Impala vs. Apache IoTDB vs. Atos Standard Common Repository vs. Interbase vs. Microsoft Access

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache IoTDB  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonInterbase  Xexclude from comparisonMicrosoft Access  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksLight-weight proven RDBMS infooriginally from BorlandMicrosoft 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.)
Primary database modelRelational DBMSTime Series DBMSDocument store
Key-value store
Relational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score4.08
Rank#75  Overall
#41  Relational DBMS
Score101.16
Rank#11  Overall
#8  Relational DBMS
Websiteimpala.apache.orgiotdb.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.embarcadero.com/­products/­interbasewww.microsoft.com/­en-us/­microsoft-365/­access
Technical documentationimpala.apache.org/­impala-docs.htmliotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.embarcadero.com/­products/­interbasedeveloper.microsoft.com/­en-us/­access
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software FoundationAtos Convergence CreatorsEmbarcaderoMicrosoft
Initial release20132018201619841992
Current release4.1.0, June 20221.1.0, April 20231703InterBase 2020, December 20191902 (16.0.11328.20222), March 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0commercialcommercialcommercial infoBundled with Microsoft Office
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaJavaCC++
Server operating systemsLinuxAll OS with a Java VM (>= 1.8)LinuxAndroid
iOS
Linux
OS X
Windows
Windows infoNot a real database server, but making use of DLLs
Data schemeyesyesSchema and schema-less with LDAP viewsyesyes
Typing infopredefined data types such as float or dateyesyesoptionalyesyes
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.nonoyesno infoexport as XML data possible
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languagenoyesyes infobut not compliant to any SQL standard
APIs and other access methodsJDBC
ODBC
JDBC
Native API
LDAPADO.NET
JDBC
ODBC
ADO.NET
DAO
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Go
Java
Python
Scala
All languages with LDAP bindings.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesnoyes infoInterbase procedure and trigger languageyes infosince Access 2010 using the ACE-engine
Triggersnoyesyesyesyes infosince Access 2010 using the ACE-engine
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infocell divisionnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesInterbase Change Viewsnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceIntegration with Hadoop and Sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoAtomic execution of specific operationsACIDACID infobut no files for transaction logging
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoMultiversion concurreny controlyes
Durability infoSupport for making data persistentyesyesyesyesyes infobut no files for transaction logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosyesLDAP bind authenticationfine grained access rights according to SQL-standardno infoa simple user-level security was built in till version Access 2003

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More resources
Apache ImpalaApache IoTDBAtos Standard Common RepositoryInterbaseMicrosoft Access
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