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

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

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGeoMesa  Xexclude from comparisonSpark SQL  Xexclude from comparisonSurrealDB  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.Spark SQL is a component on top of 'Spark Core' for structured data processingA fully ACID transactional, developer-friendly, multi-model DBMS
Primary database modelRelational DBMSSpatial DBMSRelational DBMSDocument store
Graph 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
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.86
Rank#203  Overall
#34  Document stores
#18  Graph DBMS
Websitephoenix.apache.orgwww.geomesa.orgspark.apache.org/­sqlsurrealdb.com
Technical documentationphoenix.apache.orgwww.geomesa.org/­documentation/­stable/­user/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsurrealdb.com/­docs
DeveloperApache Software FoundationCCRi and othersApache Software FoundationSurrealDB Ltd
Initial release2014201420142022
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20194.0.5, February 20243.5.0 ( 2.13), September 2023v1.1.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache License 2.0Open Source infoApache 2.0Open Source
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaScalaRust
Server operating systemsLinux
Unix
Windows
Linux
OS X
Windows
Linux
macOS
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyesschema-free
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.nonono
Secondary indexesyesyesno
SQL infoSupport of SQLyesnoSQL-like DML and DDL statementsSQL-like query language
APIs and other access methodsJDBCJDBC
ODBC
GraphQL
RESTful HTTP API
WebSocket
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Java
Python
R
Scala
Deno
Go
JavaScript (Node.js)
Rust
Server-side scripts infoStored proceduresuser defined functionsnono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingdepending on storage layeryes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
depending on storage layernone
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 layer
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
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 storagenoyes, based on authentication and database rules

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More resources
Apache PhoenixGeoMesaSpark SQLSurrealDB
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