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

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

Editorial information provided by DB-Engines
NameHawkular Metrics  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparisonSurrealDB  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 fully ACID transactional, developer-friendly, multi-model DBMS
Primary database modelTime Series DBMSRelational DBMSSearch engineRelational DBMSDocument store
Graph DBMS
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
Score1.02
Rank#190  Overall
#33  Document stores
#18  Graph DBMS
Websitewww.hawkular.orgspark.apache.org/­sqlsphinxsearch.comsplicemachine.comsurrealdb.com
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidespark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docssplicemachine.com/­how-it-workssurrealdb.com/­docs
DeveloperCommunity supported by Red HatApache Software FoundationSphinx Technologies Inc.Splice MachineSurrealDB Ltd
Initial release20142014200120142022
Current release3.5.0 ( 2.13), September 20233.5.1, February 20233.1, March 2021v1.5.0, May 2024
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
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 languageJavaScalaC++JavaRust
Server operating systemsLinux
OS X
Windows
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Linux
macOS
Windows
Data schemeschema-freeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesnoyesyes
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
Secondary indexesnonoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL-like query language (SphinxQL)yesSQL-like query language
APIs and other access methodsHTTP RESTJDBC
ODBC
Proprietary protocolJDBC
Native Spark Datasource
ODBC
GraphQL
RESTful HTTP API
WebSocket
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
Deno
Go
JavaScript (Node.js)
Rust
Server-side scripts infoStored proceduresnononoyes infoJava
Triggersyes infovia Hawkular Alertingnonoyes
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 Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandranonenoneMulti-source replication
Source-replica replication
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 integritynononoyes
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
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-standardyes, based on authentication and database rules

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Hawkular MetricsSpark SQLSphinxSplice MachineSurrealDB
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