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DBMS > Apache IoTDB vs. Lovefield vs. Microsoft Access vs. RavenDB

System Properties Comparison Apache IoTDB vs. Lovefield vs. Microsoft Access vs. RavenDB

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonLovefield  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonRavenDB  Xexclude from comparison
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 FlinkEmbeddable relational database for web apps written in pure JavaScriptMicrosoft 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 Operational and Transactional Enterprise NoSQL Document Database
Primary database modelTime Series DBMSRelational DBMSRelational DBMSDocument store
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.29
Rank#293  Overall
#133  Relational DBMS
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score2.92
Rank#101  Overall
#18  Document stores
Websiteiotdb.apache.orggoogle.github.io/­lovefieldwww.microsoft.com/­en-us/­microsoft-365/­accessravendb.net
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mddeveloper.microsoft.com/­en-us/­accessravendb.net/­docs
DeveloperApache Software FoundationGoogleMicrosoftHibernating Rhinos
Initial release2018201419922010
Current release1.1.0, April 20232.1.12, February 20171902 (16.0.11328.20222), March 20195.4, July 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0commercial infoBundled with Microsoft OfficeOpen Source infoAGPL version 3, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaScriptC++C#
Server operating systemsAll OS with a Java VM (>= 1.8)server-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariWindows infoNot a real database server, but making use of DLLsLinux
macOS
Raspberry Pi
Windows
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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.nono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languageSQL-like query language infovia JavaScript builder patternyes infobut not compliant to any SQL standardSQL-like query language (RQL)
APIs and other access methodsJDBC
Native API
ADO.NET
DAO
ODBC
OLE DB
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
JavaScriptC
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesnoyes infosince Access 2010 using the ACE-engineyes
TriggersyesUsing read-only observersyes 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)nonenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnonenoneMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infobut no files for transaction loggingACID, Cluster-wide transaction available
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes 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.yesyes infousing MemoryDB
User concepts infoAccess controlyesnono infoa simple user-level security was built in till version Access 2003Authorization levels configured per client per database

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More resources
Apache IoTDBLovefieldMicrosoft AccessRavenDB
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