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DBMS > Apache Phoenix vs. Splice Machine

System Properties Comparison Apache Phoenix vs. Splice Machine

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Our visitors often compare Apache Phoenix and Splice Machine with MySQL, Snowflake and HBase.

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.02
Rank#130  Overall
#63  Relational DBMS
Score0.54
Rank#255  Overall
#116  Relational DBMS
Websitephoenix.apache.orgsplicemachine.com
Technical documentationphoenix.apache.orgsplicemachine.com/­how-it-works
DeveloperApache Software FoundationSplice Machine
Initial release20142014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20193.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava
Server operating systemsLinux
Unix
Windows
Linux
OS X
Solaris
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyes
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.no
Secondary indexesyesyes
SQL infoSupport of SQLyesyes
APIs and other access methodsJDBCJDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyes infoJava
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache PhoenixSplice Machine
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