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DBMS > Apache IoTDB vs. Apache Phoenix vs. Microsoft Access vs. Sphinx vs. Yanza

System Properties Comparison Apache IoTDB vs. Apache Phoenix vs. Microsoft Access vs. Sphinx vs. Yanza

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonApache Phoenix  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonSphinx  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkA scale-out RDBMS with evolutionary schema built on Apache HBaseMicrosoft 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 databasesTime Series DBMS for IoT Applications
Primary database modelTime Series DBMSRelational DBMSRelational DBMSSearch engineTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websiteiotdb.apache.orgphoenix.apache.orgwww.microsoft.com/­en-us/­microsoft-365/­accesssphinxsearch.comyanza.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlphoenix.apache.orgdeveloper.microsoft.com/­en-us/­accesssphinxsearch.com/­docs
DeveloperApache Software FoundationApache Software FoundationMicrosoftSphinx Technologies Inc.Yanza
Initial release20182014199220012015
Current release1.1.0, April 20235.0-HBase2, July 2018 and 4.15-HBase1, December 20191902 (16.0.11328.20222), March 20193.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0commercial infoBundled with Microsoft OfficeOpen Source infoGPL version 2, commercial licence availablecommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenonononono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC++C++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
Unix
Windows
Windows infoNot a real database server, but making use of DLLsFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Windows
Data schemeyesyes infolate-bound, schema-on-read capabilitiesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesnono
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
Secondary indexesyesyesyesyes infofull-text index on all search fieldsno
SQL infoSupport of SQLSQL-like query languageyesyes infobut not compliant to any SQL standardSQL-like query language (SphinxQL)no
APIs and other access methodsJDBC
Native API
JDBCADO.NET
DAO
ODBC
OLE DB
Proprietary protocolHTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
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
any language that supports HTTP calls
Server-side scripts infoStored proceduresyesuser defined functionsyes infosince Access 2010 using the ACE-enginenono
Triggersyesnoyes infosince Access 2010 using the ACE-enginenoyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingnoneSharding infoPartitioning is done manually, search queries against distributed index is supportednone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication
Source-replica replication
nonenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparkHadoop integrationnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infobut no files for transaction loggingnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.yesyes
User concepts infoAccess controlyesAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyno infoa simple user-level security was built in till version Access 2003nono

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More resources
Apache IoTDBApache PhoenixMicrosoft AccessSphinxYanza
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