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DBMS > Apache Druid vs. Datomic vs. GridDB

System Properties Comparison Apache Druid vs. Datomic vs. GridDB

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonDatomic  Xexclude from comparisonGridDB  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityScalable in-memory time series database optimized for IoT and Big Data
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSTime Series DBMS
Secondary database modelsKey-value store
Relational 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
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Websitedruid.apache.orgwww.datomic.comgriddb.net
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.datomic.comdocs.griddb.net
DeveloperApache Software Foundation and contributorsCognitectToshiba Corporation
Initial release201220122013
Current release29.0.1, April 20241.0.6735, June 20235.1, August 2022
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infolimited edition freeOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, ClojureC++
Server operating systemsLinux
OS X
Unix
All OS with a Java VMLinux
Data schemeyes infoschema-less columns are supportedyesyes
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestamp
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 indexesyesyesyes
SQL infoSupport of SQLSQL for queryingnoSQL92, SQL-like TQL (Toshiba Query Language)
APIs and other access methodsJDBC
RESTful HTTP/JSON API
RESTful HTTP APIJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Clojure
Java
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoyes infoTransaction Functionsno
TriggersnoBy using transaction functionsyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednone infoBut extensive use of caching in the application peersSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesnone infoBut extensive use of caching in the application peersSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID at container level
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentyes
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 database
More information provided by the system vendor
Apache DruidDatomicGridDB
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 DruidDatomicGridDB
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