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DBMS > Citus vs. GridDB vs. Hawkular Metrics vs. Pinecone vs. ToroDB

System Properties Comparison Citus vs. GridDB vs. Hawkular Metrics vs. Pinecone vs. ToroDB

Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonGridDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonPinecone  Xexclude from comparisonToroDB  Xexclude from comparison
ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLScalable in-memory time series database optimized for IoT and Big DataHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A managed, cloud-native vector databaseA MongoDB-compatible JSON document store, built on top of PostgreSQL
Primary database modelRelational DBMSTime Series DBMSTime Series DBMSVector DBMSDocument store
Secondary database modelsDocument storeKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score3.23
Rank#92  Overall
#2  Vector DBMS
Websitewww.citusdata.comgriddb.netwww.hawkular.orgwww.pinecone.iogithub.com/­torodb/­server
Technical documentationdocs.citusdata.comdocs.griddb.netwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.pinecone.io/­docs/­overview
DeveloperToshiba CorporationCommunity supported by Red HatPinecone Systems, Inc8Kdata
Initial release20102013201420192016
Current release8.1, December 20185.1, August 2022
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availableOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache 2.0commercialOpen Source infoAGPL-V3
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++JavaJava
Server operating systemsLinuxLinuxLinux
OS X
Windows
hostedAll OS with a Java 7 VM
Data schemeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesString, Number, Booleanyes infostring, integer, double, boolean, date, object_id
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.yes infospecific XML type available, but no XML query functionalitynononono
Secondary indexesyesyesno
SQL infoSupport of SQLyes infostandard, with numerous extensionsSQL92, SQL-like TQL (Toshiba Query Language)nono
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP RESTRESTful HTTP API
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Go
Java
Python
Ruby
Python
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.nono
Triggersyesyesyes infovia Hawkular Alertingno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infobased on CassandraSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsSource-replica replicationselectable replication factor infobased on CassandraSource-replica replication
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 containersEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users can be defined per databasenoAccess rights for users and roles
More information provided by the system vendor
CitusGridDBHawkular MetricsPineconeToroDB
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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CitusGridDBHawkular MetricsPineconeToroDB
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