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DBMS > GridDB vs. HarperDB vs. Ignite vs. Linter

System Properties Comparison GridDB vs. HarperDB vs. Ignite vs. Linter

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonHarperDB  Xexclude from comparisonIgnite  Xexclude from comparisonLinter  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataUltra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.RDBMS for high security requirements
Primary database modelTime Series DBMSDocument storeKey-value store
Relational DBMS
Relational DBMS
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.02
Rank#132  Overall
#11  Time Series DBMS
Score0.55
Rank#252  Overall
#38  Document stores
Score3.64
Rank#89  Overall
#13  Key-value stores
#48  Relational DBMS
Score0.10
Rank#350  Overall
#153  Relational DBMS
Websitegriddb.netwww.harperdb.ioignite.apache.orglinter.ru
Technical documentationdocs.griddb.netdocs.harperdb.io/­docsapacheignite.readme.io/­docs
DeveloperToshiba CorporationHarperDBApache Software Foundationrelex.ru
Initial release2013201720151990
Current release5.1, August 20223.1, August 2021Apache Ignite 2.6
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial infofree community edition availableOpen Source infoApache 2.0commercial
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++Node.jsC++, Java, .NetC and C++
Server operating systemsLinuxLinux
OS X
Linux
OS X
Solaris
Windows
AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Data schemeyesdynamic schemayesyes
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyes infoJSON data typesyesyes
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 indexesyesyesyesyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)SQL-like data manipulation statementsANSI-99 for query and DML statements, subset of DDLyes
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
C#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
Server-side scripts infoStored proceduresnoCustom Functions infosince release 3.1yes (compute grid and cache interceptors can be used instead)yes infoproprietary syntax with the possibility to convert from PL/SQL
Triggersyesnoyes (cache interceptors and events)yes
Partitioning methods infoMethods for storing different data on different nodesShardingA table resides as a whole on one (or more) nodes in a clusterShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infothe nodes on which a table resides can be definedyes (replicated cache)Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnoyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelAtomic execution of specific operationsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlAccess rights for users can be defined per databaseAccess rights for users and rolesSecurity Hooks for custom implementationsfine grained access rights according to SQL-standard
More information provided by the system vendor
GridDBHarperDBIgniteLinter
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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GridDBHarperDBIgniteLinter
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