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

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

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGeoMesa  Xexclude from comparisonOceanBase  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.A distributed, high available RDBMS compatible with Oracle and MySQLSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSSpatial DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Wide column store
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
Score1.66
Rank#147  Overall
#68  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitephoenix.apache.orgwww.geomesa.orgen.oceanbase.comspark.apache.org/­sql
Technical documentationphoenix.apache.orgwww.geomesa.org/­documentation/­stable/­user/­index.htmlen.oceanbase.com/­docs/­oceanbase-databasespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationCCRi and othersOceanBase infopreviously Alibaba and Ant GroupApache Software Foundation
Initial release2014201420102014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20194.0.5, February 20244.3.0, April 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache License 2.0Open Source infoCommercial license availableOpen 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
LinuxLinux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonoyesno
Secondary indexesyesyesyesno
SQL infoSupport of SQLyesnoyesSQL-like DML and DDL statements
APIs and other access methodsJDBCJDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary native API
Table API
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Ada infoin MySQL-compatible model
C infoin Oracle- and MySQL- compatible models
C++ infoin Oracle- and MySQL- compatible models
D infoin MySQL-compatible model
Delphi infoin MySQL-compatible model
Eiffel infoin MySQL-compatible model
Erlang infoin MySQL-compatible model
Haskell infoin MySQL-compatible model
Java infoin Oracle- and MySQL- compatible models
JavaScript (Node.js) infoin MySQL-compatible model
Objective-C infoin MySQL-compatible model
OCaml infoin MySQL-compatible model
Perl infoin MySQL-compatible model
PHP infoin MySQL-compatible model
Python infoin MySQL-compatible model
Ruby infoin MySQL-compatible model
Scheme infoin MySQL-compatible model
Tcl infoin MySQL-compatible model
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsnoPL/SQL in oracle-compatible mode, MySQL Stored Procedure in mysql-compatible modeno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingdepending on storage layerhorizontal partitioning (by hash, key, range, range columns, list, and list columns)yes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
depending on storage layerMulti-source replication using Paxosnone
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 integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
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.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 storageAccess rights for users, groups and roles according to SQL-standardno
More information provided by the system vendor
Apache PhoenixGeoMesaOceanBaseSpark SQL
Specific characteristicsOceanBase Database is the world’s only native distributed database that has set new...
» more
Competitive advantagesHigh Availability : The five IDCs across three sites disaster recovery solution sets...
» more
Key customersOceanBase Database has helped over 400 customers across industries upgrade their...
» more
Market metricsTPC-C No.1 Performance , achieved a result of 707.35 million tpmC in the TPC-C benchmark...
» more
Licensing and pricing modelsMulan PubL v2 license for open source community edition. Commercial license for enterprise...
» more

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More resources
Apache PhoenixGeoMesaOceanBaseSpark SQL
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