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DBMS > Apache Druid vs. GridDB vs. Kinetica vs. Manticore Search

System Properties Comparison Apache Druid vs. GridDB vs. Kinetica vs. Manticore Search

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGridDB  Xexclude from comparisonKinetica  Xexclude from comparisonManticore Search  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataScalable in-memory time series database optimized for IoT and Big DataFully vectorized database across both GPUs and CPUsMulti-storage database for search, including full-text search.
Primary database modelRelational DBMS
Time Series DBMS
Time Series DBMSRelational DBMSSearch engine
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMS
Time Series DBMS
Time Series DBMS infousing the Manticore Columnar Library
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.29
Rank#95  Overall
#49  Relational DBMS
#7  Time Series DBMS
Score2.02
Rank#132  Overall
#11  Time Series DBMS
Score0.69
Rank#234  Overall
#107  Relational DBMS
Score0.23
Rank#317  Overall
#21  Search engines
Websitedruid.apache.orggriddb.netwww.kinetica.commanticoresearch.com
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.griddb.netdocs.kinetica.commanual.manticoresearch.com
DeveloperApache Software Foundation and contributorsToshiba CorporationKineticaManticore Software
Initial release2012201320122017
Current release29.0.1, April 20245.1, August 20227.1, August 20216.0, February 2023
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialOpen Source infoGPL version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C, C++C++
Server operating systemsLinux
OS X
Unix
LinuxLinuxFreeBSD
Linux
macOS
Windows
Data schemeyes infoschema-less columns are supportedyesyesFixed schema
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean
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.nononoCan index from XML
Secondary indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL for queryingSQL92, SQL-like TQL (Toshiba Query Language)SQL-like DML and DDL statementsSQL-like query language
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Server-side scripts infoStored proceduresnonouser defined functionsuser defined functions
Triggersnoyesyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesSource-replica replicationSource-replica replicationSynchronous replication based on Galera library
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 containersImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelnoyes infoisolated transactions for atomic changes and binary logging for safe writes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Manticore index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users can be defined per databaseAccess rights for users and roles on table levelno
More information provided by the system vendor
Apache DruidGridDBKineticaManticore Search
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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Apache DruidGridDBKineticaManticore Search
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