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DBMS > Apache Druid vs. Datomic vs. GigaSpaces vs. GridDB

System Properties Comparison Apache Druid vs. Datomic vs. GigaSpaces vs. GridDB

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonDatomic  Xexclude from comparisonGigaSpaces  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 durabilityHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsScalable in-memory time series database optimized for IoT and Big Data
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSDocument store
Object oriented DBMS infoValues are user defined objects
Time Series DBMS
Secondary database modelsGraph DBMS
Search engine
Key-value store
Relational DBMS
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
Score1.76
Rank#145  Overall
#66  Relational DBMS
Score1.02
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score2.02
Rank#132  Overall
#11  Time Series DBMS
Websitedruid.apache.orgwww.datomic.comwww.gigaspaces.comgriddb.net
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.datomic.comdocs.gigaspaces.com/­latest/­landing.htmldocs.griddb.net
DeveloperApache Software Foundation and contributorsCognitectGigaspaces TechnologiesToshiba Corporation
Initial release2012201220002013
Current release29.0.1, April 20241.0.6735, June 202315.5, September 20205.1, August 2022
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infolimited edition freeOpen Source infoApache Version 2; Commercial licenses availableOpen 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 servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, ClojureJava, C++, .NetC++
Server operating systemsLinux
OS X
Unix
All OS with a Java VMLinux
macOS
Solaris
Windows
Linux
Data schemeyes infoschema-less columns are supportedyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes 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 infoXML can be used for describing objects metadatano
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL for queryingnoSQL-99 for query and DML statementsSQL92, SQL-like TQL (Toshiba Query Language)
APIs and other access methodsJDBC
RESTful HTTP/JSON API
RESTful HTTP APIGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Clojure
Java
.Net
C++
Java
Python
Scala
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoyes infoTransaction Functionsyesno
TriggersnoBy using transaction functionsyes, event driven architectureyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednone infoBut extensive use of caching in the application peersShardingSharding
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 peersMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoMap-Reduce pattern can be built with XAP task executorsConnector 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 infoConsistency level configurable: ALL, QUORUM, ANYImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID at container level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
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 developmentyesyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnoRole-based access controlAccess rights for users can be defined per database
More information provided by the system vendor
Apache DruidDatomicGigaSpacesGridDB
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 DruidDatomicGigaSpacesGridDB
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