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DBMS > GridDB vs. Hawkular Metrics vs. Sphinx vs. YottaDB

System Properties Comparison GridDB vs. Hawkular Metrics vs. Sphinx vs. YottaDB

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonSphinx  Xexclude from comparisonYottaDB  Xexclude from comparison
DescriptionScalable 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.Open source search engine for searching in data from different sources, e.g. relational databasesA fast and solid embedded Key-value store
Primary database modelTime Series DBMSTime Series DBMSSearch engineKey-value store
Secondary database modelsKey-value store
Relational DBMS
Relational DBMS infousing the Octo plugin
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.20
Rank#317  Overall
#47  Key-value stores
Websitegriddb.netwww.hawkular.orgsphinxsearch.comyottadb.com
Technical documentationdocs.griddb.netwww.hawkular.org/­hawkular-metrics/­docs/­user-guidesphinxsearch.com/­docsyottadb.com/­resources/­documentation
DeveloperToshiba CorporationCommunity supported by Red HatSphinx Technologies Inc.YottaDB, LLC
Initial release2013201420012001
Current release5.1, August 20223.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0
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++JavaC++C
Server operating systemsLinuxLinux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Docker
Linux
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesnono
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 indexesyesnoyes infofull-text index on all search fieldsno
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)noSQL-like query language (SphinxQL)by using the Octo plugin
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP RESTProprietary protocolPostgreSQL wire protocol infousing the Octo plugin
Proprietary protocol
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Go
Java
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust
Server-side scripts infoStored proceduresnonono
Triggersyesyes infovia Hawkular Alertingno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factor infobased on Cassandranoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 dataACID at container levelnonooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlAccess rights for users can be defined per databasenonoUsers and groups based on OS-security mechanisms
More information provided by the system vendor
GridDBHawkular MetricsSphinxYottaDB
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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More resources
GridDBHawkular MetricsSphinxYottaDB
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