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DBMS > Druid vs. GridDB vs. GridGain

System Properties Comparison Druid vs. GridDB vs. GridGain

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Editorial information provided by DB-Engines
NameDruid  Xexclude from comparisonGridDB  Xexclude from comparisonGridGain  Xexclude from comparison
DescriptionOpen-source analytics data store designed for OLAP queries on timeseries dataScalable in-memory time series database optimized for IoT and Big DataGridGain is an in-memory computing platform, built on Apache Ignite
Primary database modelRelational DBMS
Time Series DBMS
Time Series DBMSKey-value store
Relational DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.83
Rank#115  Overall
#57  Relational DBMS
#7  Time Series DBMS
Score0.56
Rank#200  Overall
#10  Time Series DBMS
Score1.60
Rank#124  Overall
#22  Key-value stores
#61  Relational DBMS
Websitedruid.apache.orggriddb.netwww.gridgain.com
Technical documentationdruid.apache.org/­docs/­latest/­designgriddb.net/­en/­docs/­documents/­1-1_what-is-griddb.phpwww.gridgain.com/­docs/­latest
DeveloperMetamarkets Group and contributorsToshiba CorporationGridGain Systems, Inc.
Initial release201220132007
Current release4.2, June 2019GridGain 8.5.1
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 availablecommercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++Java, C++, .Net
Server operating systemsLinux
OS X
Unix
LinuxLinux
OS X
Solaris
Windows
Data schemeyes infoschema-less columns are supportedyesyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyes
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.nonoyes
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL support via Apache Calcite adapterSQL92 (advanced edition only), SQL-like TQL (Toshiba Query Language)ANSI-99 for query and DML statements, subset of DDL
APIs and other access methodsJSON over HTTPProprietary protocolHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnonoyes (compute grid and cache interceptors can be used instead)
Triggersnoyesyes (cache interceptors and events)
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMaster-slave replicationyes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyes (compute grid and hadoop accelerator)
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlno infoavailable via extensionsAccess rights for users can be defined per databaseSecurity Hooks for custom implementations
More information provided by the system vendor
DruidGridDBGridGain
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
DruidGridDBGridGain
Recent citations in the news

Druid Developer Ramps Cloud-Native Approach
10 December 2019, Datanami

What's Behind Lyft's Choices in Big Data Tech
10 May 2019, Datanami

Imply launches with $2M to commercialize the Druid open-source data store
19 October 2015, VentureBeat

Hadoop Creator Yahoo Finds It's Not Enough, Turns to Druid
30 July 2015, ADT Magazine

Yahoo Casts Real-Time OLAP Queries with Druid
4 August 2015, Datanami

provided by Google News

GridGain Systems Named to Deloitte 2019 Technology Fast 500™ for Second Consecutive Year
18 November 2019, GlobeNewswire

GridGain and Azul Systems Collaborate to Enable Java for Very Low-Latency Use Cases at Massive Scale
14 November 2019, GlobeNewswire

In-Memory Computing Summit North America 2019 Demonstrates How Companies Are Using In-Memory Computing to Successfully Address Digital Transformation
25 November 2019, GlobeNewswire

GridGain: Product Overview and Analysis
5 June 2019, eWeek

GridGain Experts Explain In-Memory Computing Technology and Benefits, Provide Deployment Insights at Multiple Industry Events
10 September 2019, GlobeNewswire

provided by Google News

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