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DBMS > Apache Druid vs. ArcadeDB vs. GridDB vs. QuestDB

System Properties Comparison Apache Druid vs. ArcadeDB vs. GridDB vs. QuestDB

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonArcadeDB  Xexclude from comparisonGridDB  Xexclude from comparisonQuestDB  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataFast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewrittenScalable in-memory time series database optimized for IoT and Big DataA high performance open source SQL database for time series data
Primary database modelRelational DBMS
Time Series DBMS
Document store
Graph DBMS
Key-value store
Time Series DBMS infoin next version
Time Series DBMSTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score0.10
Rank#358  Overall
#48  Document stores
#38  Graph DBMS
#52  Key-value stores
#35  Time Series DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Websitedruid.apache.orgarcadedb.comgriddb.netquestdb.io
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.arcadedb.comdocs.griddb.netquestdb.io/­docs
DeveloperApache Software Foundation and contributorsArcade DataToshiba CorporationQuestDB Technology Inc
Initial release2012202120132014
Current release29.0.1, April 2024September 20215.1, August 2022
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2.0Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++Java (Zero-GC), C++, Rust
Server operating systemsLinux
OS X
Unix
All OS with a Java VMLinuxLinux
macOS
Windows
Data schemeyes infoschema-less columns are supportedschema-freeyesyes infoschema-free via InfluxDB Line Protocol
Typing infopredefined data types such as float or dateyesyesyes 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.nononono
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL for queryingSQL-like query language, no joinsSQL92, SQL-like TQL (Toshiba Query Language)SQL with time-series extensions
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
JavaC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresnonono
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardinghorizontal partitioning (by timestamps)
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesSource-replica replicationSource-replica replicationSource-replica replication with eventual consistency
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynoyes inforelationship in graphsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID at container levelACID 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 systemAccess rights for users can be defined per database
More information provided by the system vendor
Apache DruidArcadeDBGridDBQuestDB
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Relational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Financial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» 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 DruidArcadeDBGridDBQuestDB
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