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DBMS > Apache Druid vs. GridGain vs. MonetDB vs. QuestDB

System Properties Comparison Apache Druid vs. GridGain vs. MonetDB vs. QuestDB

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGridGain  Xexclude from comparisonMonetDB  Xexclude from comparisonQuestDB  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataGridGain is an in-memory computing platform, built on Apache IgniteA relational database management system that stores data in columnsA high performance open source SQL database for time series data
Primary database modelRelational DBMS
Time Series DBMS
Key-value store
Relational DBMS
Relational DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
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
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score1.72
Rank#145  Overall
#67  Relational DBMS
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Websitedruid.apache.orgwww.gridgain.comwww.monetdb.orgquestdb.io
Technical documentationdruid.apache.org/­docs/­latest/­designwww.gridgain.com/­docs/­index.htmlwww.monetdb.org/­Documentationquestdb.io/­docs
DeveloperApache Software Foundation and contributorsGridGain Systems, Inc.MonetDB BVQuestDB Technology Inc
Initial release2012200720042014
Current release29.0.1, April 2024GridGain 8.5.1Dec2023 (11.49), December 2023
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoMozilla Public License 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, C++, .NetCJava (Zero-GC), C++, Rust
Server operating systemsLinux
OS X
Unix
Linux
OS X
Solaris
Windows
FreeBSD
Linux
OS X
Solaris
Windows
Linux
macOS
Windows
Data schemeyes infoschema-less columns are supportedyesyesyes infoschema-free via InfluxDB Line Protocol
Typing infopredefined data types such as float or dateyesyesyesyes
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.noyesno
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL for queryingANSI-99 for query and DML statements, subset of DDLyes infoSQL 2003 with some extensionsSQL with time-series extensions
APIs and other access methodsJDBC
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)yes, in SQL, C, Rno
Triggersnoyes (cache interceptors and events)yesno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingSharding via remote tableshorizontal partitioning (by timestamps)
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyes (replicated cache)none infoSource-replica replication available in experimental statusSource-replica replication with eventual consistency
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID for single-table writes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infothrough memory mapped files
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemSecurity Hooks for custom implementationsfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache DruidGridGainMonetDBQuestDB
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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More resources
Apache DruidGridGainMonetDBQuestDB
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