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DBMS > Apache Phoenix vs. Faircom DB vs. GeoMesa vs. Hawkular Metrics vs. Postgres-XL

System Properties Comparison Apache Phoenix vs. Faircom DB vs. GeoMesa vs. Hawkular Metrics vs. Postgres-XL

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonGeoMesa  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonPostgres-XL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.GeoMesa 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.Based on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelRelational DBMSKey-value store
Relational DBMS
Spatial DBMSTime Series DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Score0.86
Rank#205  Overall
#4  Spatial DBMS
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score0.53
Rank#254  Overall
#117  Relational DBMS
Websitephoenix.apache.orgwww.faircom.com/­products/­faircom-dbwww.geomesa.orgwww.hawkular.orgwww.postgres-xl.org
Technical documentationphoenix.apache.orgdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlwww.geomesa.org/­documentation/­stable/­user/­index.htmlwww.hawkular.org/­hawkular-metrics/­docs/­user-guidewww.postgres-xl.org/­documentation
DeveloperApache Software FoundationFairCom CorporationCCRi and othersCommunity supported by Red Hat
Initial release20141979201420142014 infosince 2012, originally named StormDB
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019V12, November 20205.0.0, May 202410 R1, October 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoRestricted, free version availableOpen Source infoApache License 2.0Open Source infoApache 2.0Open Source infoMozilla public license
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaANSI C, C++ScalaJavaC
Server operating systemsLinux
Unix
Windows
AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
OS X
Windows
Linux
macOS
Data schemeyes infolate-bound, schema-on-read capabilitiesschema free, schema optional, schema required, partial schema,yesschema-freeyes
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyesyesyes
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 indexesyesyesyesnoyes
SQL infoSupport of SQLyesyes, ANSI SQL with proprietary extensionsnonoyes infodistributed, parallel query execution
APIs and other access methodsJDBCADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
HTTP RESTADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
Go
Java
Python
Ruby
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresuser defined functionsyes info.Net, JavaScript, C/C++nonouser defined functions
Triggersnoyesnoyes infovia Hawkular Alertingyes
Partitioning methods infoMethods for storing different data on different nodesShardingFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningdepending on storage layerSharding infobased on Cassandrahorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).depending on storage layerselectable replication factor infobased on Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
depending on storage layerEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDtunable from ACID to Eventually ConsistentnonoACID infoMVCC
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesYes, tunable from durable to delayed durability to in-memoryyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesdepending on storage layernono
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyFine grained access rights according to SQL-standard with additional protections for filesyes infodepending on the DBMS used for storagenofine grained access rights according to SQL-standard

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More resources
Apache PhoenixFaircom DB infoformerly c-treeACEGeoMesaHawkular MetricsPostgres-XL
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