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DBMS > Dragonfly vs. Hazelcast vs. Spark SQL vs. Transbase

System Properties Comparison Dragonfly vs. Hazelcast vs. Spark SQL vs. Transbase

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Editorial information provided by DB-Engines
NameDragonfly  Xexclude from comparisonHazelcast  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  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 instanceA widely adopted in-memory data gridSpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelKey-value storeKey-value storeRelational DBMSRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.41
Rank#266  Overall
#38  Key-value stores
Score5.97
Rank#57  Overall
#6  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.11
Rank#341  Overall
#150  Relational DBMS
Websitegithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
hazelcast.comspark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationwww.dragonflydb.io/­docshazelcast.org/­imdg/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperDragonflyDB team and community contributorsHazelcastApache Software FoundationTransaction Software GmbH
Initial release2023200820141987
Current release1.0, March 20235.3.6, November 20233.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoBSL 1.1Open Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaScalaC and C++
Server operating systemsLinuxAll OS with a Java VMLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemescheme-freeschema-freeyesyes
Typing infopredefined data types such as float or datestrings, hashes, lists, sets, sorted sets, bit arraysyesyesyes
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 infothe object must implement a serialization strategynono
Secondary indexesnoyesnoyes
SQL infoSupport of SQLnoSQL-like query languageSQL-like DML and DDL statementsyes
APIs and other access methodsProprietary protocol infoRESP - REdis Serialization ProtocolJCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
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
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresLuayes infoEvent Listeners, Executor Servicesnoyes
Triggerspublish/subscribe channels provide some trigger functionalityyes infoEventsnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoReplicated MapnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of command blocks and scriptsone or two-phase-commit; repeatable reads; read commitednoyes
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.yesyesnono
User concepts infoAccess controlPassword-based authenticationRole-based access controlnofine grained access rights according to SQL-standard

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More resources
DragonflyHazelcastSpark SQLTransbase
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