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DBMS > Apache Phoenix vs. GeoMesa vs. LevelDB vs. Spark SQL

System Properties Comparison Apache Phoenix vs. GeoMesa vs. LevelDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGeoMesa  Xexclude from comparisonLevelDB  Xexclude from comparisonSpark SQL  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.Embeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSSpatial DBMSKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.78
Rank#213  Overall
#4  Spatial DBMS
Score2.35
Rank#111  Overall
#19  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitephoenix.apache.orgwww.geomesa.orggithub.com/­google/­leveldbspark.apache.org/­sql
Technical documentationphoenix.apache.orgwww.geomesa.org/­documentation/­stable/­user/­index.htmlgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationCCRi and othersGoogleApache Software Foundation
Initial release2014201420112014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20194.0.5, February 20241.23, February 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache License 2.0Open Source infoBSDOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaC++Scala
Server operating systemsLinux
Unix
Windows
Illumos
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.nononono
Secondary indexesyesyesnono
SQL infoSupport of SQLyesnonoSQL-like DML and DDL statements
APIs and other access methodsJDBCJDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsnonono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingdepending on storage layernoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
depending on storage layernonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistencydepending on storage layerImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infowith automatic compression on writesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesdepending on storage layerno
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 storagenono

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More resources
Apache PhoenixGeoMesaLevelDBSpark SQL
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