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

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

Editorial information provided by DB-Engines
NameHawkular Metrics  Xexclude from comparisonInterbase  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.Light-weight proven RDBMS infooriginally from BorlandSpark 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 DBMSRelational DBMSRelational 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
Score4.08
Rank#75  Overall
#41  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.orgwww.embarcadero.com/­products/­interbasespark.apache.org/­sqlsphinxsearch.comsplicemachine.com
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.embarcadero.com/­products/­interbasespark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperCommunity supported by Red HatEmbarcaderoApache Software FoundationSphinx Technologies Inc.Splice Machine
Initial release20141984201420012014
Current releaseInterBase 2020, December 20193.5.0 ( 2.13), September 20233.5.1, February 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen 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 languageJavaCScalaC++Java
Server operating systemsLinux
OS X
Windows
Android
iOS
Linux
OS X
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.nono infoexport as XML data possibleno
Secondary indexesnoyesnoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoyesSQL-like DML and DDL statementsSQL-like query language (SphinxQL)yes
APIs and other access methodsHTTP RESTADO.NET
JDBC
ODBC
JDBC
ODBC
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
Python
Ruby
.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby
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 infoInterbase procedure and trigger languagenonoyes infoJava
Triggersyes infovia Hawkular Alertingyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on Cassandranoneyes, 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 CassandraInterbase Change ViewsnonenoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, 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 integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoMultiversion concurreny controlyesyesyes, 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 controlnofine grained access rights according to SQL-standardnonoAccess rights for users, groups and roles according to SQL-standard

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Hawkular MetricsInterbaseSpark SQLSphinxSplice Machine
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