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DBMS > Dragonfly vs. Google Cloud Datastore vs. Netezza vs. Stardog

System Properties Comparison Dragonfly vs. Google Cloud Datastore vs. Netezza vs. Stardog

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Editorial information provided by DB-Engines
NameDragonfly  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonStardog  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 and analytics appliance part of IBM PureSystemsEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelKey-value storeDocument storeRelational DBMSGraph DBMS
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.41
Rank#266  Overall
#38  Key-value stores
Score4.47
Rank#76  Overall
#12  Document stores
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websitegithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
cloud.google.com/­datastorewww.ibm.com/­products/­netezzawww.stardog.com
Technical documentationwww.dragonflydb.io/­docscloud.google.com/­datastore/­docsdocs.stardog.com
DeveloperDragonflyDB team and community contributorsGoogleIBMStardog-Union
Initial release2023200820002010
Current release1.0, March 20237.3.0, May 2020
License infoCommercial or Open SourceOpen Source infoBSL 1.1commercialcommercialcommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
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++Java
Server operating systemsLinuxhostedLinux infoincluded in applianceLinux
macOS
Windows
Data schemescheme-freeschema-freeyesschema-free and OWL/RDFS-schema support
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.nonono infoImport/export of XML data possible
Secondary indexesnoyesyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLnoSQL-like query language (GQL)yesYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsProprietary protocol infoRESP - REdis Serialization ProtocolgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
OLE DB
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
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
C++
Fortran
Java
Lua
Perl
Python
R
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresLuausing Google App Engineyesuser defined functions and aggregates, HTTP Server extensions in Java
Triggerspublish/subscribe channels provide some trigger functionalityCallbacks using the Google Apps Enginenoyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication using PaxosSource-replica replicationMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyesno
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.Immediate Consistency in HA-Cluster
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyes inforelationships in graphs
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 TransactionsACIDACID
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)Users with fine-grained authorization conceptAccess rights for users and roles

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More resources
DragonflyGoogle Cloud DatastoreNetezza infoAlso called PureData System for Analytics by IBMStardog
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