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DBMS > Dragonfly vs. Google Cloud Datastore vs. Hive vs. Kdb

System Properties Comparison Dragonfly vs. Google Cloud Datastore vs. Hive vs. Kdb

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Editorial information provided by DB-Engines
NameDragonfly  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHive  Xexclude from comparisonKdb  Xexclude from comparison
DescriptionA drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platformdata warehouse software for querying and managing large distributed datasets, built on HadoopHigh performance Time Series DBMS
Primary database modelKey-value storeDocument storeRelational DBMSTime Series DBMS
Vector DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.49
Rank#261  Overall
#38  Key-value stores
Score4.36
Rank#72  Overall
#12  Document stores
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score7.71
Rank#49  Overall
#2  Time Series DBMS
#1  Vector DBMS
Websitegithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
cloud.google.com/­datastorehive.apache.orgkx.com
Technical documentationwww.dragonflydb.io/­docscloud.google.com/­datastore/­docscwiki.apache.org/­confluence/­display/­Hive/­Homecode.kx.com
DeveloperDragonflyDB team and community contributorsGoogleApache Software Foundation infoinitially developed by FacebookKx Systems, a division of First Derivatives plc
Initial release2023200820122000 infokdb was released 2000, kdb+ in 2003
Current release1.0, March 20233.1.3, April 20223.6, May 2018
License infoCommercial or Open SourceOpen Source infoBSL 1.1commercialOpen Source infoApache Version 2commercial infofree 32-bit version
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Javaq
Server operating systemsLinuxhostedAll OS with a Java VMLinux
OS X
Solaris
Windows
Data schemescheme-freeschema-freeyesyes
Typing infopredefined data types such as float or datestrings, hashes, lists, sets, sorted sets, bit arraysyes, details hereyesyes
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 indexesnoyesyesyes infotable attribute 'grouped'
SQL infoSupport of SQLnoSQL-like query language (GQL)SQL-like DML and DDL statementsSQL-like query language (q)
APIs and other access methodsProprietary protocol infoRESP - REdis Serialization ProtocolgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
Supported programming languagesC
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
PHP
Python
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
Server-side scripts infoStored proceduresLuausing Google App Engineyes infouser defined functions and integration of map-reduceuser defined functions
Triggerspublish/subscribe channels provide some trigger functionalityCallbacks using the Google Apps Enginenoyes infowith views
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication using Paxosselectable replication factorSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyes infoquery execution via MapReduceno infosimilar paradigm used for internal processing
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of command blocks and scriptsACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnono
Concurrency infoSupport for concurrent manipulation of datayes, strict serializability by the serveryesyesyes
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.yesnoyes
User concepts infoAccess controlPassword-based authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and rolesrights management via user accounts
More information provided by the system vendor
DragonflyGoogle Cloud DatastoreHiveKdb
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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DragonflyGoogle Cloud DatastoreHiveKdb
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