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

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

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGridDB  Xexclude from comparisonLovefield  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 DataEmbeddable relational database for web apps written in pure JavaScriptMulti-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
Time Series DBMS infousing the Manticore Columnar Library
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.29
Rank#293  Overall
#133  Relational DBMS
Score0.22
Rank#312  Overall
#21  Search engines
Websitedruid.apache.orggriddb.netgoogle.github.io/­lovefieldmanticoresearch.com
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.griddb.netgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdmanual.manticoresearch.com
DeveloperApache Software Foundation and contributorsToshiba CorporationGoogleManticore Software
Initial release2012201320142017
Current release29.0.1, April 20245.1, August 20222.1.12, February 20176.0, 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 availableOpen Source infoApache 2.0Open 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++JavaScriptC++
Server operating systemsLinux
OS X
Unix
Linuxserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariFreeBSD
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 query language infovia JavaScript builder patternSQL-like query language
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON 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
JavaScriptElixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Server-side scripts infoStored proceduresnononouser defined functions
TriggersnoyesUsing read-only observersno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingnoneSharding 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 replicationnoneSynchronous 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 containers
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelACIDyes infoisolated transactions for atomic changes and binary logging for safe writes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes 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 infousing MemoryDB
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 databasenono
More information provided by the system vendor
Apache DruidGridDBLovefieldManticore 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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Apache DruidGridDBLovefieldManticore Search
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