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DBMS > dBASE vs. GridDB vs. HEAVY.AI vs. QuestDB

System Properties Comparison dBASE vs. GridDB vs. HEAVY.AI vs. QuestDB

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Editorial information provided by DB-Engines
NamedBASE  Xexclude from comparisonGridDB  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonQuestDB  Xexclude from comparison
DescriptiondBase was one of the first databases with a development environment on PC's. Its latest version dBase V is still sold as dBase classic, which needs a DOS Emulation. The up-to-date product is dBase plus.Scalable in-memory time series database optimized for IoT and Big DataA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareA high performance open source SQL database for time series data
Primary database modelRelational DBMSTime Series DBMSRelational DBMSTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.70
Rank#44  Overall
#28  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Websitewww.dbase.comgriddb.netgithub.com/­heavyai/­heavydb
www.heavy.ai
questdb.io
Technical documentationwww.dbase.com/­support/­knowledgebasedocs.griddb.netdocs.heavy.aiquestdb.io/­docs
DeveloperAsthon TateToshiba CorporationHEAVY.AI, Inc.QuestDB Technology Inc
Initial release1979201320162014
Current releasedBASE 2019, 20195.1, August 20225.10, January 2022
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2; enterprise edition availableOpen 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++C++ and CUDAJava (Zero-GC), C++, Rust
Server operating systemsDOS infodBase Classic
Windows infodBase Pro
LinuxLinuxLinux
macOS
Windows
Data schemeyesyesyesyes 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.nonono
Secondary indexesyesyesnono
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)yesSQL with time-series extensions
APIs and other access methodsnone infoThe IDE can access other DBMS or ODBC-sources.JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
Vega
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Supported programming languagesdBase proprietary IDEC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresno infoThe IDE can access stored procedures in other database systems.nonono
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoRound robinhorizontal partitioning (by timestamps)
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationMulti-source 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 consistency within container, eventual consistency across containersImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infonot for dBase internal data, but IDE does support transactions when accessing external DBMSACID at container levelnoACID 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.yesyesyes infothrough memory mapped files
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users can be defined per databasefine grained access rights according to SQL-standard
More information provided by the system vendor
dBASEGridDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022QuestDB
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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More resources
dBASEGridDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022QuestDB
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