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DBMS > Hawkular Metrics vs. Ignite vs. Spark SQL vs. Sphinx vs. Splice Machine

System Properties Comparison Hawkular Metrics vs. Ignite vs. Spark SQL vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameHawkular Metrics  Xexclude from comparisonIgnite  Xexclude from comparisonSpark SQL  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.Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Spark SQL is a component on top of 'Spark Core' for structured data processingOpen 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 DBMSKey-value store
Relational DBMS
Relational DBMSSearch engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score3.11
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.hawkular.orgignite.apache.orgspark.apache.org/­sqlsphinxsearch.comsplicemachine.com
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guideapacheignite.readme.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperCommunity supported by Red HatApache Software FoundationApache Software FoundationSphinx Technologies Inc.Splice Machine
Initial release20142015201420012014
Current releaseApache Ignite 2.63.5.0 ( 2.13), September 20233.5.1, February 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoApache 2.0Open 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 languageJavaC++, Java, .NetScalaC++Java
Server operating systemsLinux
OS X
Windows
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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.noyesno
Secondary indexesnoyesnoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statementsSQL-like query language (SphinxQL)yes
APIs and other access methodsHTTP RESTHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
Java
Python
R
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 proceduresnoyes (compute grid and cache interceptors can be used instead)nonoyes infoJava
Triggersyes infovia Hawkular Alertingyes (cache interceptors and events)nonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraShardingyes, utilizing Spark CoreSharding 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 Cassandrayes (replicated cache)nonenoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)noYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, 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.noyesnoyes
User concepts infoAccess controlnoSecurity Hooks for custom implementationsnonoAccess rights for users, groups and roles according to SQL-standard

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Hawkular MetricsIgniteSpark SQLSphinxSplice Machine
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