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DBMS > Apache IoTDB vs. DolphinDB vs. FatDB vs. Lovefield vs. Quasardb

System Properties Comparison Apache IoTDB vs. DolphinDB vs. FatDB vs. Lovefield vs. Quasardb

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDolphinDB  Xexclude from comparisonFatDB  Xexclude from comparisonLovefield  Xexclude from comparisonQuasardb  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the 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 FlinkDolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.A .NET NoSQL DBMS that can integrate with and extend SQL Server.Embeddable relational database for web apps written in pure JavaScriptDistributed, high-performance timeseries database
Primary database modelTime Series DBMSTime Series DBMSDocument store
Key-value store
Relational DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score4.13
Rank#80  Overall
#6  Time Series DBMS
Score0.29
Rank#293  Overall
#133  Relational DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Websiteiotdb.apache.orgwww.dolphindb.comgoogle.github.io/­lovefieldquasar.ai
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.dolphindb.cn/­en/­help200/­index.htmlgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mddoc.quasar.ai/­master
DeveloperApache Software FoundationDolphinDB, IncFatCloudGooglequasardb
Initial release20182018201220142009
Current release1.1.0, April 2023v2.00.4, January 20222.1.12, February 20173.14.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree community version availablecommercialOpen Source infoApache 2.0commercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C#JavaScriptC++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
Windows
Windowsserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariBSD
Linux
OS X
Windows
Data schemeyesyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyesyes infointeger and binary
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.nononono
Secondary indexesyesyesyesyesyes infowith tags
SQL infoSupport of SQLSQL-like query languageSQL-like query languageno infoVia inetgration in SQL ServerSQL-like query language infovia JavaScript builder patternSQL-like query language
APIs and other access methodsJDBC
Native API
JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
C#JavaScript.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresyesyesyes infovia applicationsnono
Triggersyesnoyes infovia applicationsUsing read-only observersno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioningShardingnoneSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesselectable replication factornoneSource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesyesnowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes infousing MemoryDByes infoTransient mode
User concepts infoAccess controlyesAdministrators, Users, Groupsno infoCan implement custom security layer via applicationsnoCryptographically strong user authentication and audit trail

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More resources
Apache IoTDBDolphinDBFatDBLovefieldQuasardb
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