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DBMS > Dragonfly vs. EXASOL vs. Google Cloud Datastore vs. JaguarDB vs. Netezza

System Properties Comparison Dragonfly vs. EXASOL vs. Google Cloud Datastore vs. JaguarDB vs. Netezza

Editorial information provided by DB-Engines
NameDragonfly  Xexclude from comparisonEXASOL  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonJaguarDB  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  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 instanceHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformPerformant, highly scalable DBMS for AI and IoT applicationsData warehouse and analytics appliance part of IBM PureSystems
Primary database modelKey-value storeRelational DBMSDocument storeKey-value store
Vector DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.41
Rank#266  Overall
#38  Key-value stores
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.00
Rank#383  Overall
#60  Key-value stores
#13  Vector DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Websitegithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
www.exasol.comcloud.google.com/­datastorewww.jaguardb.comwww.ibm.com/­products/­netezza
Technical documentationwww.dragonflydb.io/­docswww.exasol.com/­resourcescloud.google.com/­datastore/­docswww.jaguardb.com/­support.html
DeveloperDragonflyDB team and community contributorsExasolGoogleDataJaguar, Inc.IBM
Initial release20232000200820152000
Current release1.0, March 20233.3 July 2023
License infoCommercial or Open SourceOpen Source infoBSL 1.1commercialcommercialOpen Source infoGPL V3.0commercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++ infothe server part. Clients available in other languages
Server operating systemsLinuxhostedLinuxLinux infoincluded in appliance
Data schemescheme-freeyesschema-freeyesyes
Typing infopredefined data types such as float or datestrings, hashes, lists, sets, sorted sets, bit arraysyesyes, 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.nononono
Secondary indexesnoyesyesyesyes
SQL infoSupport of SQLnoyesSQL-like query language (GQL)A subset of ANSI SQL is implemented infobut no views, foreign keys, triggersyes
APIs and other access methodsProprietary protocol infoRESP - REdis Serialization Protocol.Net
JDBC
ODBC
WebSocket
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
JDBC
ODBC
OLE DB
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
Java
Lua
Python
R
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresLuauser defined functionsusing Google App Enginenoyes
Triggerspublish/subscribe channels provide some trigger functionalityyesCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication using PaxosMulti-source replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoHadoop integrationyes infousing Google Cloud Dataflownoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate 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 Consistency
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of command blocks and scriptsACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID
Concurrency infoSupport for concurrent manipulation of datayes, strict serializability by the serveryesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnono
User concepts infoAccess controlPassword-based authenticationAccess rights for users, groups and roles according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)rights management via user accountsUsers with fine-grained authorization concept

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More resources
DragonflyEXASOLGoogle Cloud DatastoreJaguarDBNetezza infoAlso called PureData System for Analytics by IBM
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