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DBMS > Brytlyt vs. Hawkular Metrics vs. HBase vs. Solr

System Properties Comparison Brytlyt vs. Hawkular Metrics vs. HBase vs. Solr

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Editorial information provided by DB-Engines
NameBrytlyt  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHBase  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Wide-column store based on Apache Hadoop and on concepts of BigTableA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSTime Series DBMSWide column storeSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#288  Overall
#131  Relational DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score42.91
Rank#24  Overall
#3  Search engines
Websitebrytlyt.iowww.hawkular.orghbase.apache.orgsolr.apache.org
Technical documentationdocs.brytlyt.iowww.hawkular.org/­hawkular-metrics/­docs/­user-guidehbase.apache.org/­book.htmlsolr.apache.org/­resources.html
DeveloperBrytlytCommunity supported by Red HatApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software Foundation
Initial release2016201420082006
Current release5.0, August 20232.3.4, January 20219.6.0, April 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache version 2Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++ and CUDAJavaJavaJava
Server operating systemsLinux
OS X
Windows
Linux
OS X
Windows
Linux
Unix
Windows infousing Cygwin
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesschema-freeschema-free, schema definition possibleyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesoptions to bring your own types, AVROyes infosupports customizable data types and automatic typing
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.yes infospecific XML-type available, but no XML query functionality.nonoyes
Secondary indexesyesnonoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyesnonoSolr Parallel SQL Interface
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP RESTJava API
RESTful HTTP API
Thrift
Java API
RESTful HTTP/JSON API
Supported programming languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
Go
Java
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresuser defined functions infoin PL/pgSQLnoyes infoCoprocessors in JavaJava plugins
Triggersyesyes infovia Hawkular Alertingyesyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factor infobased on CassandraMulti-source replication
Source-replica replication
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency or Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoSingle row ACID (across millions of columns)optimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACyes

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More resources
BrytlytHawkular MetricsHBaseSolr
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