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DBMS > CrateDB vs. GridDB vs. Hawkular Metrics

System Properties Comparison CrateDB vs. GridDB vs. Hawkular Metrics

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonGridDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparison
DescriptionDistributed Database based on LuceneScalable 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.
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Time Series DBMSTime Series DBMS
Secondary database modelsRelational DBMSKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.76
Rank#226  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#18  Time Series DBMS
#8  Vector DBMS
Score2.00
Rank#137  Overall
#11  Time Series DBMS
Score0.07
Rank#366  Overall
#38  Time Series DBMS
Websitecratedb.comgriddb.netwww.hawkular.org
Technical documentationcratedb.com/­docsdocs.griddb.netwww.hawkular.org/­hawkular-metrics/­docs/­user-guide
DeveloperCrateToshiba CorporationCommunity supported by Red Hat
Initial release201320132014
Current release5.1, August 2022
License infoCommercial or Open SourceOpen SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageJavaC++Java
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinuxLinux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-free
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyes
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 indexesyesyesno
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitySQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP REST
Supported programming languages.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Go
Java
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions (Javascript)nono
Triggersnoyesyes infovia Hawkular Alerting
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infobased on Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelSource-replica replicationselectable replication factor infobased on Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Immediate consistency within container, eventual consistency across containersEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infounique row identifiers can be used for implementing an optimistic concurrency control strategyACID at container levelno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlrights management via user accountsAccess rights for users can be defined per databaseno
More information provided by the system vendor
CrateDBGridDBHawkular Metrics
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
GitHub trending repository
» more
Licensing and pricing modelsSee CrateDB pricing >
» more
Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
CrateDBGridDBHawkular Metrics
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