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DBMS > Apache Druid vs. Brytlyt vs. Cloudflare Workers KV vs. GridDB

System Properties Comparison Apache Druid vs. Brytlyt vs. Cloudflare Workers KV vs. GridDB

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonBrytlyt  Xexclude from comparisonCloudflare Workers KV  Xexclude from comparisonGridDB  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLA global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.Scalable in-memory time series database optimized for IoT and Big Data
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSKey-value storeTime 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
Score0.29
Rank#288  Overall
#131  Relational DBMS
Score0.32
Rank#283  Overall
#40  Key-value stores
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Websitedruid.apache.orgbrytlyt.iowww.cloudflare.com/­developer-platform/­workers-kvgriddb.net
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.brytlyt.iodevelopers.cloudflare.com/­kv/­apidocs.griddb.net
DeveloperApache Software Foundation and contributorsBrytlytCloudflareToshiba Corporation
Initial release2012201620182013
Current release29.0.1, April 20245.0, August 20235.1, August 2022
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercialOpen 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 servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++ and CUDAC++
Server operating systemsLinux
OS X
Unix
Linux
OS X
Windows
hostedLinux
Data schemeyes infoschema-less columns are supportedyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes 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.noyes infospecific XML-type available, but no XML query functionality.nono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL for queryingyesnoSQL92, SQL-like TQL (Toshiba Query Language)
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP REST
Proprietary protocol
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C
C++
Delphi
Java
Perl
Python
Tcl
C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresnouser defined functions infoin PL/pgSQLnono
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesSource-replica replicationyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoConnector 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 ConsistencyEventual ConsistencyImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID at container level
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.nonoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemfine grained access rights according to SQL-standardAccess rights for users can be defined per database
More information provided by the system vendor
Apache DruidBrytlytCloudflare Workers KVGridDB
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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More resources
Apache DruidBrytlytCloudflare Workers KVGridDB
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