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DBMS > Dragonfly vs. Hazelcast vs. Sphinx vs. Splice Machine

System Properties Comparison Dragonfly vs. Hazelcast vs. Sphinx vs. Splice Machine

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Editorial information provided by DB-Engines
NameDragonfly  Xexclude from comparisonHazelcast  Xexclude from comparisonSphinx  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 instanceA widely adopted in-memory data gridOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value storeKey-value storeSearch engineRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.49
Rank#261  Overall
#38  Key-value stores
Score5.46
Rank#61  Overall
#7  Key-value stores
Score5.95
Rank#55  Overall
#5  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitegithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
hazelcast.comsphinxsearch.comsplicemachine.com
Technical documentationwww.dragonflydb.io/­docshazelcast.org/­imdg/­docssphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperDragonflyDB team and community contributorsHazelcastSphinx Technologies Inc.Splice Machine
Initial release2023200820012014
Current release1.0, March 20235.3.6, November 20233.5.1, February 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoBSL 1.1Open Source infoApache Version 2; commercial licenses availableOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++Java
Server operating systemsLinuxAll OS with a Java VMFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemescheme-freeschema-freeyesyes
Typing infopredefined data types such as float or datestrings, hashes, lists, sets, sorted sets, bit arraysyesnoyes
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 strategy
Secondary indexesnoyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoSQL-like query languageSQL-like query language (SphinxQL)yes
APIs and other access methodsProprietary protocol infoRESP - REdis Serialization ProtocolJCache
JPA
Memcached protocol
RESTful HTTP API
Proprietary protocolJDBC
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
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresLuayes infoEvent Listeners, Executor Servicesnoyes infoJava
Triggerspublish/subscribe channels provide some trigger functionalityyes infoEventsnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoReplicated MapnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoYes, via Full Spark Integration
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 commitednoACID
Concurrency infoSupport for concurrent manipulation of datayes, strict serializability by the serveryesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlPassword-based authenticationRole-based access controlnoAccess rights for users, groups and roles according to SQL-standard

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DragonflyHazelcastSphinxSplice Machine
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