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DBMS > Dragonfly vs. Netezza vs. Splice Machine

System Properties Comparison Dragonfly vs. Netezza vs. Splice Machine

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Editorial information provided by DB-Engines
NameDragonfly  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSplice Machine  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 instanceData warehouse and analytics appliance part of IBM PureSystemsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.41
Rank#266  Overall
#38  Key-value stores
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitegithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
www.ibm.com/­products/­netezzasplicemachine.com
Technical documentationwww.dragonflydb.io/­docssplicemachine.com/­how-it-works
DeveloperDragonflyDB team and community contributorsIBMSplice Machine
Initial release202320002014
Current release1.0, March 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoBSL 1.1commercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java
Server operating systemsLinuxLinux infoincluded in applianceLinux
OS X
Solaris
Windows
Data schemescheme-freeyesyes
Typing infopredefined data types such as float or datestrings, hashes, lists, sets, sorted sets, bit arraysyesyes
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.no
Secondary indexesnoyesyes
SQL infoSupport of SQLnoyesyes
APIs and other access methodsProprietary protocol infoRESP - REdis Serialization ProtocolJDBC
ODBC
OLE DB
JDBC
Native Spark Datasource
ODBC
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
C
C++
Fortran
Java
Lua
Perl
Python
R
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresLuayesyes infoJava
Triggerspublish/subscribe channels provide some trigger functionalitynoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of command blocks and scriptsACIDACID
Concurrency infoSupport for concurrent manipulation of datayes, strict serializability by the serveryesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlPassword-based authenticationUsers with fine-grained authorization conceptAccess rights for users, groups and roles according to SQL-standard

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More resources
DragonflyNetezza infoAlso called PureData System for Analytics by IBMSplice Machine
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