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

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

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonBigObject  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 networksAnalytic DBMS for real-time computations and queriesMicrosoft 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
Relational DBMS infoa hierachical model (tree) can be imposedRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteiotdb.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorybigobject.iowww.microsoft.com/­en-us/­microsoft-365/­accesssplicemachine.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.bigobject.iodeveloper.microsoft.com/­en-us/­accesssplicemachine.com/­how-it-works
DeveloperApache Software FoundationAtos Convergence CreatorsBigObject, Inc.MicrosoftSplice Machine
Initial release20182016201519922014
Current release1.1.0, April 202317031902 (16.0.11328.20222), March 20193.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial infofree community edition availablecommercial 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

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Implementation languageJavaJavaC++Java
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
Windows infoNot a real database server, but making use of DLLsLinux
OS X
Solaris
Windows
Data schemeyesSchema and schema-less with LDAP viewsyesyesyes
Typing infopredefined data types such as float or dateyesoptionalyesyesyes
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 indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like query languagenoSQL-like DML and DDL statementsyes infobut not compliant to any SQL standardyes
APIs and other access methodsJDBC
Native API
LDAPfluentd
ODBC
RESTful HTTP API
ADO.NET
DAO
ODBC
OLE DB
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
All languages with LDAP bindingsC
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyesnoLuayes 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 configurationnoneImmediate Consistency
Foreign keys infoReferential integritynonoyes infoautomatically between fact table and dimension tablesyesyes
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 datayesyesyes infoRead/write lock on objects (tables, trees)yesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes 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.yesyesyesyes
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 RepositoryBigObjectMicrosoft AccessSplice Machine
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