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

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

Editorial information provided by DB-Engines
NameHawkular Metrics  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.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 SparkA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelTime Series DBMSRelational DBMSSearch engineRelational DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#366  Overall
#39  Time Series 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
Score0.18
Rank#332  Overall
#46  Document stores
Websitewww.hawkular.orgspark.apache.org/­sqlsphinxsearch.comsplicemachine.comgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidespark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docssplicemachine.com/­how-it-workswww.xtdb.com/­docs
DeveloperCommunity supported by Red HatApache Software FoundationSphinx Technologies Inc.Splice MachineJuxt Ltd.
Initial release20142014200120142019
Current release3.5.0 ( 2.13), September 20233.5.1, February 20233.1, March 20211.19, September 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license availableOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaC++JavaClojure
Server operating systemsLinux
OS X
Windows
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
All OS with a Java 8 (and higher) VM
Linux
Data schemeschema-freeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesnoyesyes, extensible-data-notation format
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 indexesnonoyes infofull-text index on all search fieldsyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL-like query language (SphinxQL)yeslimited SQL, making use of Apache Calcite
APIs and other access methodsHTTP RESTJDBC
ODBC
Proprietary protocolJDBC
Native Spark Datasource
ODBC
HTTP REST
JDBC
Supported programming languagesGo
Java
Python
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
Clojure
Java
Server-side scripts infoStored proceduresnononoyes infoJavano
Triggersyes infovia Hawkular Alertingnonoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on Cassandrayes, utilizing Spark CoreSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandranonenoneMulti-source replication
Source-replica replication
yes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlnononoAccess rights for users, groups and roles according to SQL-standard

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More resources
Hawkular MetricsSpark SQLSphinxSplice MachineXTDB infoformerly named Crux
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