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DBMS > Apache Impala vs. Apache IoTDB vs. Interbase vs. Machbase Neo vs. Microsoft Access

System Properties Comparison Apache Impala vs. Apache IoTDB vs. Interbase vs. Machbase Neo vs. Microsoft Access

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache IoTDB  Xexclude from comparisonInterbase  Xexclude from comparisonMachbase Neo infoFormer name was Infiniflux  Xexclude from comparisonMicrosoft Access  Xexclude from comparison
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 FlinkLight-weight proven RDBMS infooriginally from BorlandTimeSeries DBMS for AIoT and BigDataMicrosoft 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 DBMSRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score4.61
Rank#72  Overall
#39  Relational DBMS
Score0.12
Rank#339  Overall
#30  Time Series DBMS
Score104.92
Rank#11  Overall
#8  Relational DBMS
Websiteimpala.apache.orgiotdb.apache.orgwww.embarcadero.com/­products/­interbasemachbase.comwww.microsoft.com/­en-us/­microsoft-365/­access
Technical documentationimpala.apache.org/­impala-docs.htmliotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.embarcadero.com/­products/­interbasemachbase.com/­dbmsdeveloper.microsoft.com/­en-us/­access
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software FoundationEmbarcaderoMachbaseMicrosoft
Initial release20132018198420131992
Current release4.1.0, June 20221.1.0, April 2023InterBase 2020, December 2019V8.0, August 20231902 (16.0.11328.20222), March 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0commercialcommercial infofree test version availablecommercial infoBundled with Microsoft Office
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaCCC++
Server operating systemsLinuxAll OS with a Java VM (>= 1.8)Android
iOS
Linux
OS X
Windows
Linux
macOS
Windows
Windows infoNot a real database server, but making use of DLLs
Data schemeyesyesyesyesyes
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.nonono infoexport as XML data possibleno
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageyesSQL-like query languageyes infobut not compliant to any SQL standard
APIs and other access methodsJDBC
ODBC
JDBC
Native API
ADO.NET
JDBC
ODBC
gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
ADO.NET
DAO
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Go
Java
Python
Scala
.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby
C
C#
C++
Go
Java
JavaScript
PHP infovia ODBC
Python
R infovia ODBC
Scala
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesyes infoInterbase procedure and trigger languagenoyes infosince Access 2010 using the ACE-engine
Triggersnoyesyesnoyes 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)noneShardingnone
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 replicasInterbase Change Viewsselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceIntegration with Hadoop and Sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDnoACID infobut no files for transaction logging
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMultiversion concurreny controlyesyes
Durability infoSupport for making data persistentyesyesyesnoyes 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 infovolatile and lookup table
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosyesfine grained access rights according to SQL-standardsimple password-based access controlno infoa simple user-level security was built in till version Access 2003

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More resources
Apache ImpalaApache IoTDBInterbaseMachbase Neo infoFormer name was InfinifluxMicrosoft Access
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