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DBMS > GridDB vs. Hypertable vs. MarkLogic vs. PlanetScale

System Properties Comparison GridDB vs. Hypertable vs. MarkLogic vs. PlanetScale

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonHypertable  Xexclude from comparisonMarkLogic  Xexclude from comparisonPlanetScale  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionScalable in-memory time series database optimized for IoT and Big DataAn open source BigTable implementation based on distributed file systems such as HadoopOperational and transactional Enterprise NoSQL databaseScalable, distributed, serverless MySQL database platform built on top of Vitess
Primary database modelTime Series DBMSWide column storeDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMS
Secondary database modelsKey-value store
Relational DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score1.49
Rank#155  Overall
#72  Relational DBMS
Websitegriddb.netwww.progress.com/­marklogicplanetscale.com
Technical documentationdocs.griddb.netwww.progress.com/­marklogic/­documentationplanetscale.com/­docs
DeveloperToshiba CorporationHypertable Inc.MarkLogic Corp.PlanetScale
Initial release2013200920012020
Current release5.1, August 20220.9.8.11, March 201611.0, December 2022
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoGNU version 3. Commercial license availablecommercial inforestricted free version is availablecommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++C++Go
Server operating systemsLinuxLinux
OS X
Windows infoan inofficial Windows port is available
Linux
OS X
Windows
Docker
Linux
macOS
Data schemeyesschema-freeschema-free infoSchema can be enforcedyes
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampnoyesyes
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.noyes
Secondary indexesyesrestricted infoonly exact value or prefix value scansyesyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)noyes infoSQL92yes infowith proprietary extensions
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
C++ API
Thrift
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++
Java
Perl
PHP
Python
Ruby
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnonoyes infovia XQuery or JavaScriptyes infoproprietary syntax
Triggersyesnoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factor on file system levelyesMulti-source replication
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 jobsyesyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynononoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelnoACID infocan act as a resource manager in an XA/JTA transactionACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
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.yesyes, with Range Indexesyes
User concepts infoAccess controlAccess rights for users can be defined per databasenoRole-based access control at the document and subdocument levelsUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
GridDBHypertableMarkLogicPlanetScale
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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GridDBHypertableMarkLogicPlanetScale
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