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DBMS > Apache Druid vs. BoltDB vs. GridDB vs. Kinetica vs. SwayDB

System Properties Comparison Apache Druid vs. BoltDB vs. GridDB vs. Kinetica vs. SwayDB

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonBoltDB  Xexclude from comparisonGridDB  Xexclude from comparisonKinetica  Xexclude from comparisonSwayDB  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAn embedded key-value store for Go.Scalable in-memory time series database optimized for IoT and Big DataFully vectorized database across both GPUs and CPUsAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelRelational DBMS
Time Series DBMS
Key-value storeTime Series DBMSRelational DBMSKey-value store
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMS
Time Series DBMS
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
Score0.74
Rank#220  Overall
#31  Key-value stores
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.00
Rank#382  Overall
#59  Key-value stores
Websitedruid.apache.orggithub.com/­boltdb/­boltgriddb.netwww.kinetica.comswaydb.simer.au
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.griddb.netdocs.kinetica.com
DeveloperApache Software Foundation and contributorsToshiba CorporationKineticaSimer Plaha
Initial release20122013201320122018
Current release29.0.1, April 20245.1, August 20227.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoMIT LicenseOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialOpen Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGoC++C, C++Scala
Server operating systemsLinux
OS X
Unix
BSD
Linux
OS X
Solaris
Windows
LinuxLinux
Data schemeyes infoschema-less columns are supportedschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesnoyes infonumerical, string, blob, geometry, boolean, timestampyesno
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.nonononono
Secondary indexesyesnoyesyesno
SQL infoSupport of SQLSQL for queryingnoSQL92, SQL-like TQL (Toshiba Query Language)SQL-like DML and DDL statementsno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
GoC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
Java
Kotlin
Scala
Server-side scripts infoStored proceduresnononouser defined functionsno
Triggersnonoyesyes 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-basednoneShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesnoneSource-replica replicationSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate consistency within container, eventual consistency across containersImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACID at container levelnoAtomic execution of operations
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.nonoyesyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnoAccess rights for users can be defined per databaseAccess rights for users and roles on table levelno
More information provided by the system vendor
Apache DruidBoltDBGridDBKineticaSwayDB
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
Apache DruidBoltDBGridDBKineticaSwayDB
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