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DBMS > Apache Phoenix vs. GeoMesa vs. Hawkular Metrics vs. HEAVY.AI vs. Postgres-XL

System Properties Comparison Apache Phoenix vs. GeoMesa vs. Hawkular Metrics vs. HEAVY.AI vs. Postgres-XL

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGeoMesa  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonPostgres-XL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelRelational DBMSSpatial DBMSTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score0.86
Rank#205  Overall
#4  Spatial DBMS
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score0.53
Rank#254  Overall
#117  Relational DBMS
Websitephoenix.apache.orgwww.geomesa.orgwww.hawkular.orggithub.com/­heavyai/­heavydb
www.heavy.ai
www.postgres-xl.org
Technical documentationphoenix.apache.orgwww.geomesa.org/­documentation/­stable/­user/­index.htmlwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.heavy.aiwww.postgres-xl.org/­documentation
DeveloperApache Software FoundationCCRi and othersCommunity supported by Red HatHEAVY.AI, Inc.
Initial release20142014201420162014 infosince 2012, originally named StormDB
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20195.0.0, May 20245.10, January 202210 R1, October 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache License 2.0Open Source infoApache 2.0Open Source infoApache Version 2; enterprise edition availableOpen Source infoMozilla public license
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 languageJavaScalaJavaC++ and CUDAC
Server operating systemsLinux
Unix
Windows
Linux
OS X
Windows
LinuxLinux
macOS
Data schemeyes infolate-bound, schema-on-read capabilitiesyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nonononoyes infoXML type, but no XML query functionality
Secondary indexesyesyesnonoyes
SQL infoSupport of SQLyesnonoyesyes infodistributed, parallel query execution
APIs and other access methodsJDBCHTTP RESTJDBC
ODBC
Thrift
Vega
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Go
Java
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresuser defined functionsnononouser defined functions
Triggersnonoyes infovia Hawkular Alertingnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingdepending on storage layerSharding infobased on CassandraSharding infoRound robinhorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
depending on storage layerselectable replication factor infobased on CassandraMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistencydepending on storage layerEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnononoACID infoMVCC
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.yesdepending on storage layernoyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyyes infodepending on the DBMS used for storagenofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Apache PhoenixGeoMesaHawkular MetricsHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Postgres-XL
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