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DBMS > Hawkular Metrics vs. LokiJS vs. Riak KV vs. Sphinx vs. Splice Machine

System Properties Comparison Hawkular Metrics vs. LokiJS vs. Riak KV vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameHawkular Metrics  Xexclude from comparisonLokiJS  Xexclude from comparisonRiak KV  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.In-memory JavaScript DBMSDistributed, fault tolerant key-value storeOpen 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 modelTime Series DBMSDocument storeKey-value store infowith links between data sets and object tags for the creation of secondary indexesSearch engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score0.49
Rank#260  Overall
#42  Document stores
Score4.01
Rank#79  Overall
#9  Key-value stores
Score5.95
Rank#55  Overall
#5  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.hawkular.orggithub.com/­techfort/­LokiJSsphinxsearch.comsplicemachine.com
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidetechfort.github.io/­LokiJSwww.tiot.jp/­riak-docs/­riak/­kv/­latestsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperCommunity supported by Red HatOpenSource, formerly Basho TechnologiesSphinx Technologies Inc.Splice Machine
Initial release20142014200920012014
Current release3.2.0, December 20223.5.1, February 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0Open SourceOpen Source infoApache version 2, commercial enterprise editionOpen 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 languageJavaJavaScriptErlangC++Java
Server operating systemsLinux
OS X
Windows
server-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesnononoyes
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 indexesnoyes infovia viewsrestrictedyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnononoSQL-like query language (SphinxQL)yes
APIs and other access methodsHTTP RESTJavaScript APIHTTP API
Native Erlang Interface
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
Python
Ruby
JavaScriptC infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
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 proceduresnoView functions in JavaScriptErlangnoyes infoJava
Triggersyes infovia Hawkular Alertingyesyes infopre-commit hooks and post-commit hooksnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandranoneSharding infono "single point of failure"Sharding 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 nodesselectable replication factor infobased on Cassandranoneselectable replication factornoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
noneEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono infolinks between data sets can be storednoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoatomic operations within a single collection possiblenonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes infoSerialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.yesyes 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.noyesyes
User concepts infoAccess controlnonoyes, using Riak SecuritynoAccess rights for users, groups and roles according to SQL-standard

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More resources
Hawkular MetricsLokiJSRiak KVSphinxSplice Machine
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