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DBMS > Apache Phoenix vs. PieCloudDB vs. Splice Machine vs. Yanza

System Properties Comparison Apache Phoenix vs. PieCloudDB vs. Splice Machine vs. Yanza

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonPieCloudDB  Xexclude from comparisonSplice Machine  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA cloud-native analytic database platform with new technologoy for elastic MPPOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkTime Series DBMS for IoT Applications
Primary database modelRelational DBMSRelational DBMSRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.25
Rank#304  Overall
#138  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitephoenix.apache.orgwww.openpie.comsplicemachine.comyanza.com
Technical documentationphoenix.apache.orgsplicemachine.com/­how-it-works
DeveloperApache Software FoundationOpenPieSplice MachineYanza
Initial release201420142015
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20192.1, January 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoAGPL 3.0, commercial license availablecommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenoyesnono infobut mainly used as a service provided by Yanza
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
hostedLinux
OS X
Solaris
Windows
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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 indexesyesyesyesno
SQL infoSupport of SQLyesyesyesno
APIs and other access methodsJDBCCLI Client
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
HTTP API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Java
PL/SQL
Python
R
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
any language that supports HTTP calls
Server-side scripts infoStored proceduresuser defined functionsuser defined functionsyes infoJavano
Triggersnonoyesyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesShardingyesShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
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.yesyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyUser Roles and pluggable authentication with full SQL StandardAccess rights for users, groups and roles according to SQL-standardno
More information provided by the system vendor
Apache PhoenixPieCloudDBSplice MachineYanza
Specific characteristicsPieCloudDB, OpenPie's flagship product, is a cutting-edge cloud-native data warehouse....
» more
Competitive advantagesExtreme Elastic: PieCloudDB utilizes a cutting-edge eMPP cloud-native architecture...
» more
Typical application scenariosPieCloudDB is ideal for Data mining applications that require extreme scalability...
» more
Key customersSail-Cloud China Shipbuilding Group Haizhou System Soochow Securities ​etc.,
» more
Licensing and pricing modelsPieCloudDB Community Edition: Community License, Free Download, Self-Hosted Deployment;...
» more

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More resources
Apache PhoenixPieCloudDBSplice MachineYanza
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Recent citations in the news

Supercharge SQL on Your Data in Apache HBase with Apache Phoenix | Amazon Web Services
2 June 2016, AWS Blog

Azure #HDInsight Apache Phoenix now supports Zeppelin
16 August 2018, azure.microsoft.com

Bridge the SQL-NoSQL gap with Apache Phoenix
4 February 2016, InfoWorld

Apache Calcite, FreeMarker, Gora, Phoenix, and Solr updated
27 March 2017, SDTimes.com

Hortonworks Starts Hadoop Summit with Data Platform Update -- ADTmag
28 June 2016, ADT Magazine

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Machine learning data pipeline outfit Splice Machine files for insolvency
26 August 2021, The Register

Splice Machine Launches the Splice Machine Feature Store to Simplify Feature Engineering and Democratize Machine ...
19 January 2021, PR Newswire

Splice Machine Launches Feature Store to Simplify Feature Engineering
19 January 2021, Datanami

How Splice Machine's Data Platform for Intelligent Apps Works
29 September 2020, eWeek

Distributed SQL System Review: Snowflake vs Splice Machine
18 September 2019, Towards Data Science

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