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DBMS > Apache Phoenix vs. Ingres vs. Microsoft Azure Synapse Analytics vs. Spark SQL vs. Splice Machine

System Properties Comparison Apache Phoenix vs. Ingres vs. Microsoft Azure Synapse Analytics vs. Spark SQL vs. Splice Machine

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonIngres  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSpark SQL  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseWell established RDBMSElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerSpark SQL is a component on top of 'Spark Core' for structured data processingOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score3.80
Rank#82  Overall
#44  Relational DBMS
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitephoenix.apache.orgwww.actian.com/­databases/­ingresazure.microsoft.com/­services/­synapse-analyticsspark.apache.org/­sqlsplicemachine.com
Technical documentationphoenix.apache.orgdocs.actian.com/­ingresdocs.microsoft.com/­azure/­synapse-analyticsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsplicemachine.com/­how-it-works
DeveloperApache Software FoundationActian CorporationMicrosoftApache Software FoundationSplice Machine
Initial release20141974 infooriginally developed at University Berkely in early 1970s201620142014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 201911.2, May 20223.5.0 ( 2.13), September 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCC++ScalaJava
Server operating systemsLinux
Unix
Windows
AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
hostedLinux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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 infobut tools for importing/exporting data from/to XML-files availablenono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLyesyesyesSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
ADO.NET
JDBC
ODBC
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C#
Java
PHP
Java
Python
R
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyesTransact SQLnoyes infoJava
Triggersnoyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding, horizontal partitioningyes, utilizing Spark CoreShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Ingres ReplicatoryesnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoMVCCyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyfine grained access rights according to SQL-standardyesnoAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache PhoenixIngresMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSpark SQLSplice Machine
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