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DBMS > DataFS vs. GridDB vs. OpenEdge vs. QuestDB

System Properties Comparison DataFS vs. GridDB vs. OpenEdge vs. QuestDB

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Editorial information provided by DB-Engines
NameDataFS  Xexclude from comparisonGridDB  Xexclude from comparisonOpenEdge  Xexclude from comparisonQuestDB  Xexclude from comparison
DescriptionAll data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.Scalable in-memory time series database optimized for IoT and Big DataApplication development environment with integrated database management systemA high performance open source SQL database for time series data
Primary database modelObject oriented DBMSTime Series DBMSRelational DBMSTime Series DBMS
Secondary database modelsGraph DBMSKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.09
Rank#360  Overall
#17  Object oriented DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score3.45
Rank#85  Overall
#46  Relational DBMS
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Websitenewdatabase.comgriddb.netwww.progress.com/­openedgequestdb.io
Technical documentationdev.mobiland.com/­Overview.xspdocs.griddb.netdocumentation.progress.com/­output/­ua/­OpenEdge_latestquestdb.io/­docs
DeveloperMobiland AGToshiba CorporationProgress Software CorporationQuestDB Technology Inc
Initial release2018201319842014
Current release1.1.263, October 20225.1, August 2022OpenEdge 12.2, March 2020
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java (Zero-GC), C++, Rust
Server operating systemsWindowsLinuxAIX
HP-UX
Linux
Solaris
Windows
Linux
macOS
Windows
Data schemeClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)yesyesyes infoschema-free via InfluxDB Line Protocol
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesyes
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.nonoyesno
Secondary indexesnoyesyesno
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)yes infoclose to SQL 92SQL with time-series extensions
APIs and other access methods.NET Client API
Proprietary client DLL
WinRT client
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Supported programming languages.Net
C
C#
C++
VB.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Progress proprietary ABL (Advanced Business Language)C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresnoyesno
Triggersno, except callback-events from server when changes happenedyesyesno
Partitioning methods infoMethods for storing different data on different nodesProprietary Sharding systemShardinghorizontal partitioning infosince Version 11.4horizontal partitioning (by timestamps)
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationSource-replica replication with eventual consistency
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelACIDACID for single-table writes
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.noyesnoyes infothrough memory mapped files
User concepts infoAccess controlWindows-ProfileAccess rights for users can be defined per databaseUsers and groups
More information provided by the system vendor
DataFSGridDBOpenEdgeQuestDB
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Relational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Financial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
DataFSGridDBOpenEdgeQuestDB
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