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DBMS > Hawkular Metrics vs. LeanXcale vs. Microsoft Azure SQL Database vs. RethinkDB vs. Spark SQL

System Properties Comparison Hawkular Metrics vs. LeanXcale vs. Microsoft Azure SQL Database vs. RethinkDB vs. Spark SQL

Editorial information provided by DB-Engines
NameHawkular Metrics  Xexclude from comparisonLeanXcale  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonRethinkDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesDatabase as a Service offering with high compatibility to Microsoft SQL ServerDBMS for the Web with a mechanism to push updated query results to applications in realtime.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelTime Series DBMSKey-value store
Relational DBMS
Relational DBMSDocument storeRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score0.29
Rank#291  Overall
#41  Key-value stores
#132  Relational DBMS
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score2.74
Rank#105  Overall
#19  Document stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.hawkular.orgwww.leanxcale.comazure.microsoft.com/­en-us/­products/­azure-sql/­databaserethinkdb.comspark.apache.org/­sql
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.microsoft.com/­en-us/­azure/­azure-sqlrethinkdb.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCommunity supported by Red HatLeanXcaleMicrosoftThe Linux Foundation infosince July 2017Apache Software Foundation
Initial release20142015201020092014
Current releaseV122.4.1, August 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C++Scala
Server operating systemsLinux
OS X
Windows
hostedLinux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes infostring, binary, float, bool, date, geometryyes
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.noyesnono
Secondary indexesnoyesyesno
SQL infoSupport of SQLnoyes infothrough Apache DerbyyesnoSQL-like DML and DDL statements
APIs and other access methodsHTTP RESTJDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
ADO.NET
JDBC
ODBC
JDBC
ODBC
Supported programming languagesGo
Java
Python
Ruby
C
Java
Scala
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
C infocommunity-supported driver
C# infocommunity-supported driver
C++ infocommunity-supported driver
Clojure infocommunity-supported driver
Dart infocommunity-supported driver
Erlang infocommunity-supported driver
Go infocommunity-supported driver
Haskell infocommunity-supported driver
Java infoofficial driver
JavaScript (Node.js) infoofficial driver
Lisp infocommunity-supported driver
Lua infocommunity-supported driver
Objective-C infocommunity-supported driver
Perl infocommunity-supported driver
PHP infocommunity-supported driver
Python infoofficial driver
Ruby infoofficial driver
Scala infocommunity-supported driver
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoTransact SQLno
Triggersyes infovia Hawkular AlertingyesClient-side triggers through changefeedsno
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraSharding inforange basedyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on Cassandrayes, with always 3 replicas availableSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDAtomic single-document operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoMVCC basedyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlnofine grained access rights according to SQL-standardyes infousers and table-level permissionsno

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More resources
Hawkular MetricsLeanXcaleMicrosoft Azure SQL Database infoformerly SQL AzureRethinkDBSpark SQL
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