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DBMS > Elasticsearch vs. Hawkular Metrics vs. Spark SQL

System Properties Comparison Elasticsearch vs. Hawkular Metrics vs. Spark SQL

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Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricHawkular 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 processing
Primary database modelSearch engineTime Series DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score134.78
Rank#7  Overall
#1  Search engines
Score0.04
Rank#374  Overall
#38  Time Series DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitewww.elastic.co/­elasticsearchwww.hawkular.orgspark.apache.org/­sql
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlwww.hawkular.org/­hawkular-metrics/­docs/­user-guidespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperElasticCommunity supported by Red HatApache Software Foundation
Initial release201020142014
Current release8.6, January 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoElastic LicenseOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaScala
Server operating systemsAll OS with a Java VMLinux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes
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 indexesyes infoAll search fields are automatically indexednono
SQL infoSupport of SQLSQL-like query languagenoSQL-like DML and DDL statements
APIs and other access methodsJava API
RESTful HTTP/JSON API
HTTP RESTJDBC
ODBC
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
Go
Java
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesnono
Triggersyes infoby using the 'percolation' featureyes infovia Hawkular Alertingno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on Cassandrayes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factor infobased on Cassandranone
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop Connectorno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Memcached and Redis integrationnono
User concepts infoAccess controlnono

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More resources
ElasticsearchHawkular MetricsSpark SQL
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