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DBMS > Dragonfly vs. Hawkular Metrics vs. Percona Server for MongoDB vs. Sphinx vs. Splice Machine

System Properties Comparison Dragonfly vs. Hawkular Metrics vs. Percona Server for MongoDB vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameDragonfly  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonPercona Server for MongoDB  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 instanceHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A drop-in replacement for MongoDB Community Edition with enterprise-grade features.Open 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 storeTime Series DBMSDocument storeSearch engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.44
Rank#255  Overall
#38  Key-value stores
Score0.01
Rank#377  Overall
#39  Time Series DBMS
Score0.50
Rank#250  Overall
#39  Document stores
Score5.97
Rank#56  Overall
#5  Search engines
Score0.54
Rank#244  Overall
#114  Relational DBMS
Websitegithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
www.hawkular.orgwww.percona.com/­mongodb/­software/­percona-server-for-mongodbsphinxsearch.comsplicemachine.com
Technical documentationwww.dragonflydb.io/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.percona.com/­percona-distribution-for-mongodbsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperDragonflyDB team and community contributorsCommunity supported by Red HatPerconaSphinx Technologies Inc.Splice Machine
Initial release20232014201520012014
Current release1.0, March 20233.4.10-2.10, November 20173.5.1, February 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoBSL 1.1Open Source infoApache 2.0Open Source infoGPL Version 2Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC++C++Java
Server operating systemsLinuxLinux
OS X
Windows
LinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemescheme-freeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datestrings, hashes, lists, sets, sorted sets, bit arraysyesyesnoyes
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
Secondary indexesnonoyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnononoSQL-like query language (SphinxQL)yes
APIs and other access methodsProprietary protocol infoRESP - REdis Serialization ProtocolHTTP RESTproprietary protocol using JSONProprietary 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
Go
Java
Python
Ruby
Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk
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 proceduresLuanoJavaScriptnoyes infoJava
Triggerspublish/subscribe channels provide some trigger functionalityyes infovia Hawkular Alertingnonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraShardingSharding 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 replicationselectable replication factor infobased on CassandraSource-replica replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of command blocks and scriptsnononoACID
Concurrency infoSupport for concurrent manipulation of datayes, strict serializability by the serveryesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes 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.yesnoyes infovia In-Memory Engineyes
User concepts infoAccess controlPassword-based authenticationnoAccess rights for users and rolesnoAccess rights for users, groups and roles according to SQL-standard

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More resources
DragonflyHawkular MetricsPercona Server for MongoDBSphinxSplice Machine
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