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DBMS > Apache IoTDB vs. Atos Standard Common Repository vs. LevelDB vs. Microsoft Access vs. Splice Machine

System Properties Comparison Apache IoTDB vs. Atos Standard Common Repository vs. LevelDB vs. Microsoft Access vs. Splice Machine

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonLevelDB  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonSplice Machine  Xexclude from comparison
This system has been discontinued and will be removed 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 FlinkHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesMicrosoft 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 SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelTime Series DBMSDocument store
Key-value store
Key-value storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score2.25
Rank#115  Overall
#19  Key-value stores
Score101.16
Rank#11  Overall
#8  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteiotdb.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorygithub.com/­google/­leveldbwww.microsoft.com/­en-us/­microsoft-365/­accesssplicemachine.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mddeveloper.microsoft.com/­en-us/­accesssplicemachine.com/­how-it-works
DeveloperApache Software FoundationAtos Convergence CreatorsGoogleMicrosoftSplice Machine
Initial release20182016201119922014
Current release1.1.0, April 202317031.23, February 20211902 (16.0.11328.20222), March 20193.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoBSDcommercial infoBundled with Microsoft OfficeOpen Source infoAGPL 3.0, commercial license available
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 languageJavaJavaC++C++Java
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxIllumos
Linux
OS X
Windows
Windows infoNot a real database server, but making use of DLLsLinux
OS X
Solaris
Windows
Data schemeyesSchema and schema-less with LDAP viewsschema-freeyesyes
Typing infopredefined data types such as float or dateyesoptionalnoyesyes
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.noyesno
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLSQL-like query languagenonoyes infobut not compliant to any SQL standardyes
APIs and other access methodsJDBC
Native API
LDAPADO.NET
DAO
ODBC
OLE DB
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
All languages with LDAP bindingsC++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyesnonoyes infosince Access 2010 using the ACE-engineyes infoJava
Triggersyesyesnoyes infosince Access 2010 using the ACE-engineyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infocell divisionnonenoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesnonenoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparknonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsnoACID infobut no files for transaction loggingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infowith automatic compression on writesyes infobut no files for transaction loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlyesLDAP bind authenticationnono infoa simple user-level security was built in till version Access 2003Access rights for users, groups and roles according to SQL-standard

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More resources
Apache IoTDBAtos Standard Common RepositoryLevelDBMicrosoft AccessSplice Machine
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