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DBMS > DolphinDB vs. FatDB vs. Spark SQL vs. Yaacomo

System Properties Comparison DolphinDB vs. FatDB vs. Spark SQL vs. Yaacomo

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Editorial information provided by DB-Engines
NameDolphinDB  Xexclude from comparisonFatDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonYaacomo  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionDolphinDB 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.Spark SQL is a component on top of 'Spark Core' for structured data processingOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelTime Series DBMSDocument store
Key-value store
Relational DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.23
Rank#82  Overall
#6  Time Series DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitewww.dolphindb.comspark.apache.org/­sqlyaacomo.com
Technical documentationdocs.dolphindb.cn/­en/­help200/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDolphinDB, IncFatCloudApache Software FoundationQ2WEB GmbH
Initial release2018201220142009
Current releasev2.00.4, January 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree community version availablecommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C#Scala
Server operating systemsLinux
Windows
WindowsLinux
OS X
Windows
Android
Linux
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesyesnoyes
SQL infoSupport of SQLSQL-like query languageno infoVia inetgration in SQL ServerSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
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
JDBC
ODBC
JDBC
ODBC
Supported programming languagesC#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
C#Java
Python
R
Scala
Server-side scripts infoStored proceduresyesyes infovia applicationsno
Triggersnoyes infovia applicationsnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingyes, utilizing Spark Corehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factornoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlAdministrators, Users, Groupsno infoCan implement custom security layer via applicationsnofine grained access rights according to SQL-standard

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DolphinDBFatDBSpark SQLYaacomo
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