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DBMS > Apache Phoenix vs. LeanXcale vs. Spark SQL

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

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonLeanXcale  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesSpark 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
Score3.04
Rank#107  Overall
#55  Relational DBMS
Score0.22
Rank#318  Overall
#44  Key-value stores
#142  Relational DBMS
Score20.62
Rank#36  Overall
#22  Relational DBMS
Websitephoenix.apache.orgwww.leanxcale.comspark.apache.org/­sql
Technical documentationphoenix.apache.orgspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationLeanXcaleApache Software Foundation
Initial release201420152014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20193.3.0 ( 2.13), June 2022
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 languageJavaScala
Server operating systemsLinux
Unix
Windows
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyes
Typing infopredefined data types such as float or dateyesyes
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.nono
Secondary indexesyesno
SQL infoSupport of SQLyesyes infothrough Apache DerbySQL-like DML and DDL statements
APIs and other access methodsJDBCJDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
Java
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsno
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
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-tenancyno
More information provided by the system vendor
Apache PhoenixLeanXcaleSpark SQL
Specific characteristicsFull ACID and full SQL operational database with analytical queries over operational...
» more
Competitive advantagesLinear scalability upto 100s of nodes (tested with 100 nodes and TPC-C).
» more
Typical application scenariosHybrid Transactional-Analytical Processing (HTAP) requiring an operational database...
» more
Key customersbanking/finance/fintech, telco, insurance, traveltech, M2M/IoT, retail
» more
Market metrics15 beta testers
» more
Licensing and pricing modelsannual fee covering license and support based on number of physical cores
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Apache PhoenixLeanXcaleSpark SQL
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