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DBMS > Apache Phoenix vs. GridGain vs. Spark SQL

System Properties Comparison Apache Phoenix vs. GridGain vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGridGain  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseGridGain is an in-memory computing platform, built on Apache IgniteSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitephoenix.apache.orgwww.gridgain.comspark.apache.org/­sql
Technical documentationphoenix.apache.orgwww.gridgain.com/­docs/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationGridGain Systems, Inc.Apache Software Foundation
Initial release201420072014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019GridGain 8.5.13.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, C++, .NetScala
Server operating systemsLinux
Unix
Windows
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.noyesno
Secondary indexesyesyesno
SQL infoSupport of SQLyesANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statements
APIs and other access methodsJDBCHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyes (compute grid and cache interceptors can be used instead)no
Triggersnoyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yes (replicated cache)none
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyes (compute grid and hadoop accelerator)
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancySecurity Hooks for custom implementationsno

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More resources
Apache PhoenixGridGainSpark SQL
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